{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import numpy as np\n",
    "# 设置设备，如果有GPU那么使用默认的GPU设备（一般为GPU0）\n",
    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
    "\n",
    "# 固定随机数种子\n",
    "seed = 20070504\n",
    "torch.manual_seed(seed)\n",
    "np.random.seed(seed)\n",
    "if torch.cuda.is_available():\n",
    "    torch.cuda.manual_seed(seed)\n",
    "    torch.cuda.manual_seed_all(seed)  # 为所有GPU设置种子"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 数据的信息已经三合一，约定数据为processed_normed_data，归一化信息为processed_normed_data_para，空间信息在space_data.csv中\n",
    "path = \"/home/duxiangyu/data/kdd/\"\n",
    "\n",
    "# 位置信息类型，如果是经纬度则为'lal'，坐标为'coor'，无位置信息为'None'\n",
    "space_data_mode = 'coor'\n",
    "\n",
    "# 用于预测的数据名称\n",
    "dataname = \"kdd\"\n",
    "\n",
    "# 总特征数\n",
    "feateures = 3\n",
    "\n",
    "# 输入，隐藏层，输出维度\n",
    "dims = (feateures, 128, 1)\n",
    "\n",
    "# 风机数量\n",
    "num_nodes = 134\n",
    "\n",
    "# 一般base为风速所在行，target选取差分\n",
    "target_feature = 1\n",
    "base_feature = 0\n",
    "\n",
    "# 被预测的风机编号为id，下标为(id - 1)\n",
    "target_turbine = 0\n",
    "\n",
    "# 批大小和训练次数\n",
    "batch_size = 64\n",
    "num_epochs = 10\n",
    "\n",
    "# 回望窗口长度和预测长度\n",
    "seq = 30\n",
    "pred_len = 1\n",
    "\n",
    "# 时间模块的层数\n",
    "num_layer = 2\n",
    "\n",
    "# 学习率\n",
    "lr = 0.001\n",
    "\n",
    "# 是否使用静态图\n",
    "static_graph = False\n",
    "\n",
    "# 是否使用特征模块\n",
    "feature_block = True\n",
    "\n",
    "# 是否进行纯时间序列预测\n",
    "only_time_block = False\n",
    "\n",
    "# 是否进行单点预测\n",
    "single_point = True\n",
    "\n",
    "# log文件路径\n",
    "logfile = f'./log/{dataname}.log'\n",
    "\n",
    "from src.utils.log import init_log\n",
    "init_log(logfile=logfile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/duxiangyu/grugcn/src/loader/turbine_data_loader.py:33: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
      "  data = torch.load(cachefile)\n"
     ]
    }
   ],
   "source": [
    "# 加载特征数据\n",
    "from src.loader.turbine_data_loader import load_turbine_data\n",
    "data = load_turbine_data('cache_data', dataname, path + \"normed_processed_data\", logfile)\n",
    "# data = data[:10000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 加载空间信息\n",
    "from src.loader.space_graph_loader import load_space_data\n",
    "space_graph = load_space_data(path + \"space_data.csv\", num_nodes, space_data_mode, para_lambda=2000, limit=3000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from src.data.turbine_dataset import TurbineDataset\n",
    "dataset = TurbineDataset(data, space_graph, seq, pred_len, target_turbine, target_feature, base_feature, logfile, single_point)\n",
    "trainset, valset, testset = dataset.split((0.75, 0.125, 0.125))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data import DataLoader\n",
    "trainloader = DataLoader(trainset, batch_size=batch_size, shuffle=True)\n",
    "valloader = DataLoader(valset, batch_size, shuffle=True)\n",
    "testloader = DataLoader(testset, batch_size, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "# 从norm文件中拿到denorm需要的参数\n",
    "data_denorm_path = path + \"normed_processed_data_para\"\n",
    "files = os.listdir(data_denorm_path)\n",
    "files.sort()\n",
    "file = files[target_turbine]\n",
    "df = pd.read_csv(os.path.join(data_denorm_path, file))\n",
    "target_mean = df.iloc[target_feature][\"Mean\"]\n",
    "target_std = df.iloc[target_feature][\"Std\"]\n",
    "\n",
    "base_mean = df.iloc[base_feature][\"Mean\"]\n",
    "base_std = df.iloc[base_feature][\"Std\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from src.model.model import Model\n",
    "# 加载模型\n",
    "model = Model(target_turbine, \n",
    "              target_feature, \n",
    "              num_nodes=num_nodes, \n",
    "              num_layer=num_layer, \n",
    "              seq=seq, \n",
    "              pred_len=pred_len, \n",
    "              dims=dims, \n",
    "              static_graph=static_graph, \n",
    "              feature_block=feature_block, \n",
    "              only_time_block=only_time_block, \n",
    "              single_point=single_point\n",
    "              )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from src.trainer import Trainer\n",
    "from torch.nn import HuberLoss, MSELoss\n",
    "optimizer=torch.optim.Adam(filter(lambda p: p.requires_grad, model.parameters()), lr=lr)\n",
    "trainer = Trainer(dataname, model=model, optimizer=optimizer, criterion=HuberLoss(), device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "training epoch 0: 100%|██████████| 414/414 [02:05<00:00,  3.30it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1, Training Loss: 0.41501162953422843\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "valing: 100%|██████████| 69/69 [00:05<00:00, 11.95it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valloss is 0.19363232799198316\n",
      "best loss from 1.7976931348623157e+308 to 0.19363232799198316\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "training epoch 1: 100%|██████████| 414/414 [02:05<00:00,  3.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2, Training Loss: 0.414467911609417\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "valing: 100%|██████████| 69/69 [00:05<00:00, 12.05it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valloss is 0.1938718329521193\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "training epoch 2: 100%|██████████| 414/414 [02:05<00:00,  3.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3, Training Loss: 0.4148550721038367\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "valing: 100%|██████████| 69/69 [00:05<00:00, 12.02it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valloss is 0.19477578652077826\n",
      "early stopping 1/3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "training epoch 3: 100%|██████████| 414/414 [02:04<00:00,  3.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4, Training Loss: 0.415082764186433\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "valing: 100%|██████████| 69/69 [00:05<00:00, 12.04it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valloss is 0.18968957867743313\n",
      "best loss from 0.19363232799198316 to 0.18968957867743313\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "training epoch 4: 100%|██████████| 414/414 [02:04<00:00,  3.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5, Training Loss: 0.40756299177517635\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "valing: 100%|██████████| 69/69 [00:05<00:00, 12.01it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valloss is 0.18940228828485461\n",
      "best loss from 0.18968957867743313 to 0.18940228828485461\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "training epoch 5: 100%|██████████| 414/414 [02:04<00:00,  3.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6, Training Loss: 0.40571547972695265\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "valing: 100%|██████████| 69/69 [00:05<00:00, 12.02it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valloss is 0.1891550792084224\n",
      "best loss from 0.18940228828485461 to 0.1891550792084224\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "training epoch 6: 100%|██████████| 414/414 [02:04<00:00,  3.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7, Training Loss: 0.4053118597122206\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "valing: 100%|██████████| 69/69 [00:05<00:00, 12.04it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valloss is 0.18852167187825494\n",
      "best loss from 0.1891550792084224 to 0.18852167187825494\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "training epoch 7: 100%|██████████| 414/414 [02:04<00:00,  3.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8, Training Loss: 0.40601115770961926\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "valing: 100%|██████████| 69/69 [00:05<00:00, 12.02it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valloss is 0.18937902422486871\n",
      "early stopping 1/3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "training epoch 8: 100%|██████████| 414/414 [02:04<00:00,  3.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9, Training Loss: 0.4028051257817354\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "valing: 100%|██████████| 69/69 [00:05<00:00, 12.02it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valloss is 0.19026223883248758\n",
      "early stopping 2/3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "training epoch 9: 100%|██████████| 414/414 [02:04<00:00,  3.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10, Training Loss: 0.40351464905312673\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "valing: 100%|██████████| 69/69 [00:05<00:00, 12.03it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valloss is 0.19018215740072555\n",
      "early stopping 3/3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "trainer.train(trainloader, valloader, target_mean=target_mean, target_std=target_std, base_mean=base_mean, base_std=base_std, epochs=num_epochs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_3148968/1592008717.py:2: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
      "  trainer.model = torch.load(f'pths/{dataname}.pth')\n"
     ]
    }
   ],
   "source": [
    "# 加载最好的模型\n",
    "trainer.model = torch.load(f'pths/{dataname}.pth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "torch.Size([64, 134, 1])\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
      "tensor([0.3384, 0.3392, 0.3224], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n"
     ]
    }
   ],
   "source": [
    "# 测试并可视化结果\n",
    "y_p, y_t = trainer.predict(testloader, target_mean, target_std, base_mean, base_std, True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1874951343559504\n",
      "0.307507976450048\n",
      "3.9074833393096924\n"
     ]
    }
   ],
   "source": [
    "mseloss = 0\n",
    "maeloss = 0\n",
    "maxloss = 0\n",
    "\n",
    "for t, p in zip(y_t, y_p):\n",
    "    mseloss += (t - p) ** 2\n",
    "    maeloss += abs(t - p)\n",
    "        \n",
    "    if abs(p - t) > maxloss:\n",
    "        maxloss = abs(p - t)\n",
    "        \n",
    "print(mseloss / len(y_t))\n",
    "print(maeloss / len(y_t))\n",
    "print(maxloss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[7.359999656677246, 7.62999963760376, 7.490000247955322, 6.399999618530273, 6.119999408721924, 5.900000095367432, 5.559999465942383, 5.869999885559082, 5.039999961853027, 5.569999694824219, 5.669999599456787, 5.180000305175781, 5.579999923706055, 5.069999694824219, 6.199999809265137, 6.71999979019165, 7.5199995040893555, 7.3299994468688965, 7.069999694824219, 7.499999523162842, 6.369999885559082, 6.25, 7.039999961853027, 6.820000171661377, 6.529999732971191, 6.059999942779541, 6.309999942779541, 6.420000076293945, 5.840000152587891, 5.929999828338623, 5.839999675750732, 5.089999675750732, 4.619999885559082, 4.409999847412109, 4.009999752044678, 4.399999618530273, 4.5799994468688965, 4.949999809265137, 5.009999752044678, 4.349999904632568, 4.799999713897705, 3.989999771118164, 3.489999771118164, 3.7099997997283936, 4.420000076293945, 4.050000190734863, 4.37999963760376, 3.8500001430511475, 4.329999923706055, 4.199999809265137, 4.169999599456787, 4.289999961853027, 4.309999942779541, 3.929999828338623, 4.659999847412109, 5.199999809265137, 4.329999923706055, 5.0, 5.440000057220459, 5.579999923706055, 5.710000038146973, 5.820000171661377, 5.749999523162842, 5.929999828338623, 5.659999847412109, 5.699999809265137, 5.319999694824219, 4.909999847412109, 4.619999885559082, 4.269999980926514, 4.380000114440918, 4.099999904632568, 4.289999961853027, 4.539999961853027, 4.039999961853027, 4.029999732971191, 4.479999542236328, 5.210000038146973, 5.25, 5.730000019073486, 5.519999980926514, 5.300000190734863, 5.089999675750732, 4.7699995040893555, 4.940000057220459, 4.9599995613098145, 5.019999980926514, 4.820000171661377, 5.509999752044678, 4.710000038146973, 5.110000133514404, 5.259999752044678, 4.899999618530273, 5.2099995613098145, 5.03000020980835, 5.509999752044678, 5.899999618530273, 6.1399993896484375, 6.139999866485596, 6.259999752044678, 6.739999771118164, 6.579999923706055, 6.539999961853027, 6.259999752044678, 6.679999828338623, 6.710000038146973, 6.920000076293945, 7.039999961853027, 7.489999771118164, 7.549999713897705, 7.2699995040893555, 6.670000076293945, 6.200000286102295, 5.62999963760376, 5.729999542236328, 5.28000020980835, 5.809999465942383, 5.630000114440918, 5.509999752044678, 6.25, 6.309999942779541, 6.679999828338623, 7.779999732971191, 6.909999847412109, 6.239999771118164, 6.2099995613098145, 6.960000038146973, 6.260000228881836, 7.0199995040893555, 6.539999961853027, 6.389999866485596, 7.069999694824219, 7.419999599456787, 7.510000228881836, 7.899999618530273, 7.979999542236328, 7.1399993896484375, 6.869999885559082, 6.519999980926514, 6.28000020980835, 7.059999465942383, 7.679999828338623, 7.199999809265137, 7.769999980926514, 8.09999942779541, 7.8199992179870605, 8.50999927520752, 8.600000381469727, 8.200000762939453, 8.729999542236328, 8.50999927520752, 7.710000038146973, 7.570000171661377, 7.569999694824219, 7.289999485015869, 7.029999732971191, 6.669999599456787, 6.950000286102295, 7.210000038146973, 6.970000267028809, 6.899999618530273, 6.619999408721924, 6.989999771118164, 7.229999542236328, 7.090000152587891, 7.199999809265137, 7.149999618530273, 7.259999752044678, 6.699999809265137, 6.460000038146973, 6.539999961853027, 7.0, 6.800000190734863, 5.989999771118164, 5.979999542236328, 6.170000076293945, 6.119999885559082, 5.769999980926514, 5.179999828338623, 5.46999979019165, 5.099999904632568, 5.210000038146973, 5.260000228881836, 4.909999847412109, 4.71999979019165, 4.849999904632568, 4.75, 4.679999828338623, 4.369999885559082, 4.309999942779541, 3.6499998569488525, 3.9599997997283936, 3.93999981880188, 4.46999979019165, 5.259999752044678, 5.609999656677246, 5.779999732971191, 5.559999942779541, 5.779999732971191, 6.4599995613098145, 6.190000057220459, 5.599999904632568, 5.759999752044678, 6.419999599456787, 6.389999866485596, 5.630000114440918, 5.7699995040893555, 5.699999809265137, 5.299999713897705, 5.279999732971191, 5.279999732971191, 5.279999732971191, 5.309999942779541, 5.679999828338623, 5.949999809265137, 6.039999961853027, 6.300000190734863, 6.829999923706055, 7.039999961853027, 7.46999979019165, 8.050000190734863, 8.539999961853027, 8.829999923706055, 8.670000076293945, 9.149999618530273, 9.179999351501465, 9.430000305175781, 8.600000381469727, 9.450000762939453, 9.359999656677246, 8.429999351501465, 7.750000476837158, 7.050000190734863, 7.069999694824219, 6.859999656677246, 6.759999752044678, 7.579999923706055, 7.420000076293945, 7.090000152587891, 6.829999923706055, 6.900000095367432, 7.1399993896484375, 7.37999963760376, 6.820000171661377, 7.5199995040893555, 8.65999984741211, 8.4399995803833, 8.65999984741211, 8.769999504089355, 8.619999885559082, 8.4399995803833, 8.90999984741211, 8.130000114440918, 5.72999906539917, 5.869999885559082, 6.46999979019165, 6.799999713897705, 8.34999942779541, 9.269999504089355, 8.559999465942383, 8.029999732971191, 8.50999927520752, 8.460000038146973, 8.390000343322754, 8.979999542236328, 9.169999122619629, 8.770000457763672, 8.699999809265137, 9.269999504089355, 8.799999237060547, 8.859999656677246, 8.109999656677246, 8.649999618530273, 8.929999351501465, 9.09000015258789, 8.739999771118164, 8.569999694824219, 9.289999961853027, 9.0600004196167, 8.899999618530273, 9.0, 9.609999656677246, 9.389999389648438, 8.389999389648438, 7.469999313354492, 6.949999809265137, 6.829999923706055, 6.699999809265137, 6.679999828338623, 7.569999694824219, 8.09999942779541, 8.299999237060547, 8.049999237060547, 7.900000095367432, 8.1899995803833, 8.129999160766602, 7.939999103546143, 8.149999618530273, 7.789999485015869, 8.670000076293945, 7.710000038146973, 8.960000038146973, 8.010000228881836, 8.710000038146973, 8.329999923706055, 8.170000076293945, 8.470000267028809, 8.180000305175781, 8.030000686645508, 8.019999504089355, 7.749999523162842, 7.260000228881836, 7.729999542236328, 7.6999993324279785, 7.449999809265137, 7.960000038146973, 7.5, 7.559999942779541, 7.649999618530273, 7.979999542236328, 7.749999523162842, 7.599999904632568, 7.650000095367432, 7.179999828338623, 7.439999580383301, 7.809999465942383, 7.739999771118164, 7.589999675750732, 7.809999942779541, 7.940000057220459, 7.309999465942383, 7.75, 7.789999961853027, 7.71999979019165, 7.619999885559082, 7.0, 6.630000114440918, 6.720000267028809, 7.389999866485596, 7.599999904632568, 6.699999809265137, 6.519999980926514, 7.21999979019165, 7.369999885559082, 6.389999866485596, 5.480000019073486, 5.820000171661377, 5.699999809265137, 6.029999732971191, 7.029999732971191, 8.369999885559082, 9.059999465942383, 7.749999523162842, 8.350000381469727, 8.029999732971191, 8.549999237060547, 8.44999885559082, 8.380000114440918, 8.600000381469727, 8.660000801086426, 8.59000015258789, 8.610000610351562, 8.4399995803833, 8.589999198913574, 8.779999732971191, 8.0, 7.619999885559082, 7.130000114440918, 7.590000152587891, 8.75, 8.25, 7.449999809265137, 7.659999847412109, 7.269999980926514, 7.539999961853027, 7.550000190734863, 7.679999828338623, 7.579999923706055, 7.940000057220459, 8.079999923706055, 8.15999984741211, 8.039999961853027, 7.869999885559082, 7.769999980926514, 7.539999485015869, 7.820000171661377, 7.809999465942383, 7.980000019073486, 7.549999713897705, 6.979999542236328, 6.7099995613098145, 6.369999885559082, 6.759999752044678, 7.359999656677246, 7.369999885559082, 7.349999904632568, 6.849999904632568, 6.429999828338623, 6.329999923706055, 6.159999847412109, 6.649999618530273, 7.199999809265137, 6.549999713897705, 6.529999732971191, 6.329999923706055, 6.529999732971191, 6.21999979019165, 6.169999599456787, 6.019999980926514, 5.96999979019165, 5.980000019073486, 5.5, 4.960000038146973, 4.610000133514404, 4.909999847412109, 4.849999904632568, 5.069999694824219, 4.549999713897705, 5.509999752044678, 6.049999713897705, 6.079999923706055, 6.369999885559082, 6.429999828338623, 6.019999980926514, 6.019999980926514, 5.659999847412109, 5.710000038146973, 6.460000038146973, 6.650000095367432, 5.949999809265137, 6.009999752044678, 6.309999942779541, 6.070000171661377, 5.949999809265137, 6.089999675750732, 5.759999752044678, 5.229999542236328, 5.130000114440918, 4.809999465942383, 4.570000171661377, 4.009999752044678, 3.989999771118164, 3.9099998474121094, 4.480000019073486, 4.650000095367432, 5.21999979019165, 4.809999942779541, 4.759999752044678, 4.799999713897705, 4.87999963760376, 4.87999963760376, 4.46999979019165, 4.299999713897705, 4.560000419616699, 4.519999980926514, 4.429999828338623, 4.159999847412109, 3.739999771118164, 3.8899998664855957, 3.6599998474121094, 3.3899998664855957, 3.0799999237060547, 2.859999895095825, 2.490000009536743, 2.999999761581421, 2.5099997520446777, 2.1600000858306885, 2.3499999046325684, 2.119999885559082, 1.369999885559082, 1.5999999046325684, 1.4399999380111694, 1.5800000429153442, 1.8100001811981201, 1.6999996900558472, 1.929999828338623, 1.6299998760223389, 1.7399996519088745, 1.9499998092651367, 2.049999952316284, 2.3499996662139893, 2.5299999713897705, 2.5, 2.569999933242798, 2.379999876022339, 2.4799997806549072, 2.809999704360962, 3.549999713897705, 4.249999523162842, 4.25, 4.25, 4.730000019073486, 5.039999961853027, 4.630000114440918, 4.649999618530273, 4.729999542236328, 4.559999942779541, 4.599999904632568, 4.210000038146973, 3.75, 3.5799999237060547, 3.6399998664855957, 3.489999771118164, 3.619999885559082, 3.929999828338623, 3.819999933242798, 3.669999599456787, 3.7199997901916504, 3.5999999046325684, 3.7300000190734863, 3.989999771118164, 4.319999694824219, 4.049999713897705, 3.8799996376037598, 4.210000038146973, 4.5, 4.269999980926514, 3.9200000762939453, 4.119999885559082, 4.279999732971191, 3.5799996852874756, 3.2699999809265137, 3.6500000953674316, 3.93999981880188, 3.7599997520446777, 3.93999981880188, 3.619999885559082, 3.8399999141693115, 4.199999809265137, 3.6599998474121094, 3.7599997520446777, 3.669999837875366, 3.4099998474121094, 3.549999952316284, 3.609999656677246, 3.4700000286102295, 3.429999828338623, 3.3999998569488525, 3.3299999237060547, 3.129999876022339, 2.559999942779541, 2.569999933242798, 2.440000057220459, 2.109999895095825, 1.8799998760223389, 2.0399999618530273, 1.7799997329711914, 1.7000001668930054, 1.589999794960022, 1.5399999618530273, 1.6299997568130493, 1.929999589920044, 1.6999998092651367, 1.6899998188018799, 1.75, 2.0399999618530273, 2.2599997520446777, 2.0799996852874756, 2.0799999237060547, 2.1599998474121094, 2.7099997997283936, 2.7599997520446777, 2.2200000286102295, 2.2299997806549072, 2.3899998664855957, 2.5399999618530273, 2.9200000762939453, 2.9599997997283936, 2.9100000858306885, 2.549999952316284, 1.9500000476837158, 1.8900001049041748, 1.5599998235702515, 1.4500001668930054, 1.630000352859497, 1.619999647140503, 1.1499998569488525, 0.9599996209144592, 1.1200000047683716, 1.4899998903274536, 1.5800000429153442, 1.6400001049041748, 1.529999852180481, 1.4600000381469727, 0.9699997901916504, 0.7999997735023499, 0.7499997019767761, 0.5799995064735413, 0.44999992847442627, 0.26999980211257935, 0.34999996423721313, 0.49999991059303284, 0.8500000238418579, 1.0199998617172241, 1.4299999475479126, 1.5499998331069946, 1.8299999237060547, 2.1299996376037598, 2.3999998569488525, 2.879999876022339, 3.2899999618530273, 3.5899999141693115, 4.259999752044678, 3.2599997520446777, 4.109999656677246, 3.7799997329711914, 3.5899996757507324, 3.6499996185302734, 3.9499998092651367, 4.289999961853027, 4.269999980926514, 3.8499999046325684, 4.289999961853027, 4.360000133514404, 4.249999523162842, 4.659999847412109, 4.130000114440918, 3.9000000953674316, 3.7299997806549072, 3.5399997234344482, 3.450000047683716, 3.2199997901916504, 3.7699997425079346, 3.3899998664855957, 3.8499999046325684, 3.990000009536743, 3.559999704360962, 3.5399999618530273, 3.6399998664855957, 3.3899998664855957, 3.249999761581421, 2.9499998092651367, 2.1600000858306885, 3.3399996757507324, 4.579999923706055, 4.849999904632568, 3.4099998474121094, 3.8999998569488525, 3.8399999141693115, 4.779999732971191, 5.179999828338623, 4.509999752044678, 3.5999996662139893, 2.679999828338623, 1.9499998092651367, 2.0299999713897705, 3.2599997520446777, 3.7199997901916504, 3.739999771118164, 3.5799996852874756, 2.9499998092651367, 1.8199999332427979, 1.7999999523162842, 2.3299999237060547, 1.7999999523162842, 1.5999999046325684, 2.119999885559082, 2.4599997997283936, 2.0399997234344482, 1.739999771118164, 1.7799997329711914, 1.6100002527236938, 1.3199999332427979, 1.3449996709823608, 1.3699997663497925, 1.4399999380111694, 1.190000057220459, 0.8799996376037598, 0.9299996495246887, 0.8099998235702515, 0.5699999332427979, 0.3300001621246338, 0.2699999213218689, 0.5799999833106995, 0.5899999141693115, 0.8700001239776611, 1.209999918937683, 1.2199995517730713, 1.3599997758865356, 1.2500001192092896, 1.6200000047683716, 1.559999942779541, 2.2900002002716064, 2.6999998092651367, 3.249999761581421, 1.8799997568130493, 1.5499998331069946, 1.0999999046325684, 1.0099998712539673, 1.3000001907348633, 1.4799997806549072, 1.399999737739563, 1.3500001430511475, 1.369999885559082, 1.529999852180481, 1.4800000190734863, 1.3499997854232788, 1.5899999141693115, 1.6399998664855957, 1.529999852180481, 1.6100000143051147, 1.9999998807907104, 1.999999761581421, 1.929999828338623, 2.299999713897705, 2.490000009536743, 2.619999885559082, 2.6599998474121094, 3.18999981880188, 3.999999761581421, 3.880000114440918, 2.919999837875366, 2.239999771118164, 2.2699997425079346, 2.6399998664855957, 3.239999771118164, 3.6599998474121094, 3.129999876022339, 3.3299999237060547, 3.8999998569488525, 4.579999923706055, 5.449999809265137, 5.369999885559082, 4.690000057220459, 4.339999675750732, 4.5799994468688965, 3.690000057220459, 2.9100000858306885, 2.7199997901916504, 2.700000047683716, 2.9499998092651367, 3.009999990463257, 2.8499996662139893, 2.4600000381469727, 2.559999704360962, 2.5299999713897705, 2.1700000762939453, 2.1500000953674316, 1.929999828338623, 1.8599998950958252, 1.7499998807907104, 2.259999990463257, 2.1599998474121094, 1.7199997901916504, 2.239999771118164, 2.2299997806549072, 1.8299998044967651, 1.4399996995925903, 1.340000033378601, 1.070000171661377, 0.9400001764297485, 0.8800000548362732, 1.1999995708465576, 1.029999852180481, 0.9400002360343933, 1.0200001001358032, 1.0699999332427979, 0.8100001811981201, 0.3899999260902405, 0.3599998652935028, 0.3599996566772461, 0.6799996495246887, 0.8100003004074097, 0.2799999713897705, 0.7500002384185791, 0.5299994945526123, 0.899999737739563, 1.0600000619888306, 0.9599999785423279, 1.0099999904632568, 1.440000295639038, 1.340000033378601, 1.3300001621246338, 2.259999990463257, 2.8799996376037598, 2.8299999237060547, 4.019999980926514, 4.920000076293945, 5.25, 5.739999771118164, 5.779999732971191, 6.869999885559082, 7.399999618530273, 7.479999542236328, 7.449999809265137, 7.109999656677246, 7.0799994468688965, 7.21999979019165, 6.609999656677246, 6.46999979019165, 6.419999599456787, 5.990000247955322, 5.869999885559082, 6.210000038146973, 6.360000133514404, 6.279999732971191, 6.229999542236328, 6.610000133514404, 6.889999866485596, 6.569999694824219, 6.679999828338623, 6.859999656677246, 6.729999542236328, 6.550000190734863, 7.039999485015869, 7.179999828338623, 7.739999771118164, 7.559999942779541, 7.109999656677246, 7.739999771118164, 7.439999580383301, 7.309999465942383, 7.75, 8.050000190734863, 7.930000305175781, 8.269999504089355, 8.530000686645508, 9.019999504089355, 8.819999694824219, 8.179999351501465, 8.180000305175781, 8.289999961853027, 8.529999732971191, 8.869999885559082, 8.529999732971191, 8.34000015258789, 8.470000267028809, 9.119999885559082, 9.380000114440918, 9.420000076293945, 9.510000228881836, 9.40000057220459, 9.15999984741211, 8.720000267028809, 8.409998893737793, 7.940000057220459, 7.929999351501465, 7.619999885559082, 7.239999771118164, 7.559999942779541, 7.399999618530273, 8.049999237060547, 7.880000114440918, 7.599999904632568, 7.340000152587891, 7.189999580383301, 6.87999963760376, 6.549999713897705, 6.759999752044678, 6.699999809265137, 6.87999963760376, 7.619999885559082, 7.739999771118164, 6.909999847412109, 7.339999675750732, 7.259999752044678, 7.829999923706055, 7.809999942779541, 6.96999979019165, 7.579999923706055, 7.369999885559082, 6.690000057220459, 6.46999979019165, 6.589999675750732, 6.799999713897705, 6.599999904632568, 6.049999713897705, 6.089999675750732, 5.419999599456787, 5.380000114440918, 5.689999580383301, 5.849999904632568, 5.849999904632568, 5.199999809265137, 5.460000038146973, 6.230000019073486, 5.760000228881836, 5.389999866485596, 5.989999771118164, 4.669999599456787, 4.519999980926514, 4.699999809265137, 4.859999656677246, 5.109999656677246, 4.999999523162842, 4.690000057220459, 4.809999465942383, 4.239999771118164, 4.21999979019165, 4.109999656677246, 4.509999752044678, 4.809999942779541, 4.769999980926514, 4.349999904632568, 4.940000057220459, 4.199999809265137, 4.439999580383301, 4.509999752044678, 4.4599995613098145, 4.699999809265137, 4.899999618530273, 4.819999694824219, 5.309999465942383, 4.929999828338623, 5.519999980926514, 5.25, 5.650000095367432, 5.449999809265137, 5.5, 6.300000190734863, 6.689999580383301, 6.369999408721924, 7.109999656677246, 7.909999847412109, 6.759999752044678, 6.7099995613098145, 6.170000076293945, 5.889999866485596, 7.149999618530273, 8.049999237060547, 7.730000019073486, 7.789999485015869, 6.679999828338623, 6.109999656677246, 7.199999809265137, 7.87999963760376, 7.599999904632568, 7.670000076293945, 8.440000534057617, 9.219999313354492, 10.529998779296875, 11.220000267028809, 11.409998893737793, 12.319999694824219, 11.510000228881836, 11.880000114440918, 12.34999942779541, 12.280000686645508, 11.869999885559082, 11.210000038146973, 11.1899995803833, 10.910000801086426, 10.819999694824219, 10.09000015258789, 9.350000381469727, 9.699999809265137, 9.9399995803833, 10.559999465942383, 10.139999389648438, 10.249999046325684, 10.300000190734863, 10.50999927520752, 9.710000038146973, 9.390000343322754, 8.729999542236328, 9.089999198913574, 8.819999694824219, 8.199999809265137, 8.309999465942383, 8.559999465942383, 9.089999198913574, 8.40000057220459, 8.989999771118164, 8.920000076293945, 9.0600004196167, 8.649999618530273, 7.569999694824219, 7.579999923706055, 7.119999885559082, 7.829999923706055, 6.519999980926514, 4.670000076293945, 3.930000066757202, 3.549999713897705, 3.4799997806549072, 2.859999656677246, 3.109999895095825, 2.879999876022339, 2.739999771118164, 2.690000057220459, 1.6599998474121094, 1.4899998903274536, 0.38999998569488525, 0.8399999141693115, 1.619999647140503, 3.2899999618530273, 2.7300000190734863, 1.4299999475479126, 1.3599998950958252, 2.080000162124634, 1.309999942779541, 1.5199999809265137, 3.1399996280670166, 4.329999923706055, 4.75, 3.6399998664855957, 2.819999933242798, 4.46999979019165, 4.759999752044678, 5.139999866485596, 4.670000076293945, 3.7699999809265137, 3.7799999713897705, 4.319999694824219, 2.9699997901916504, 2.4700000286102295, 2.18999981880188, 2.2699997425079346, 2.179999828338623, 3.1100001335144043, 3.2099997997283936, 3.3299999237060547, 2.7300000190734863, 2.450000047683716, 2.4699997901916504, 3.0399997234344482, 3.689999580383301, 3.309999942779541, 4.339999675750732, 4.899999618530273, 5.2099995613098145, 5.210000038146973, 5.440000057220459, 5.920000076293945, 6.269999980926514, 5.789999961853027, 6.179999828338623, 6.639999866485596, 6.309999942779541, 6.070000171661377, 6.299999713897705, 5.949999809265137, 5.909999847412109, 5.460000038146973, 5.5, 5.789999961853027, 5.46999979019165, 5.259999752044678, 5.489999771118164, 5.799999713897705, 6.359999656677246, 6.389999866485596, 6.529999732971191, 5.049999713897705, 5.009999752044678, 5.499999523162842, 5.690000057220459, 5.309999942779541, 6.130000114440918, 6.449999809265137, 6.829999923706055, 7.420000076293945, 6.840000152587891, 7.539999961853027, 7.320000171661377, 7.449999809265137, 6.210000038146973, 5.720000267028809, 5.37999963760376, 5.749999523162842, 5.519999980926514, 5.150000095367432, 4.869999408721924, 4.259999752044678, 4.119999885559082, 3.9699997901916504, 4.579999923706055, 4.840000152587891, 4.909999847412109, 5.299999713897705, 5.7099995613098145, 5.28000020980835, 4.669999599456787, 5.190000057220459, 5.28000020980835, 5.449999809265137, 6.909999847412109, 6.869999885559082, 6.559999942779541, 6.539999961853027, 6.159999847412109, 5.739999771118164, 5.049999713897705, 4.099999904632568, 4.130000114440918, 4.579999923706055, 3.549999952316284, 2.359999656677246, 2.799999952316284, 3.8199996948242188, 3.4499998092651367, 2.609999656677246, 2.4599997997283936, 2.299999713897705, 3.379999876022339, 2.7799999713897705, 2.809999942779541, 3.0699996948242188, 3.629999876022339, 3.3999998569488525, 3.3399999141693115, 3.359999895095825, 3.879999876022339, 3.369999885559082, 3.009999990463257, 3.0299997329711914, 3.3499996662139893, 3.179999828338623, 3.3399999141693115, 3.109999895095825, 3.359999895095825, 3.3899998664855957, 2.2299997806549072, 1.5399997234344482, 1.2199997901916504, 1.339999794960022, 1.6000001430511475, 1.119999885559082, 0.9499998688697815, 0.679999828338623, 0.4200003147125244, 0.39999958872795105, 0.49999961256980896, 1.0799999237060547, 1.559999942779541, 1.7000001668930054, 1.4499998092651367, 1.4700002670288086, 1.8799999952316284, 2.8899998664855957, 1.9399998188018799, 1.929999828338623, 2.119999885559082, 1.7299998998641968, 1.5299999713897705, 1.5699999332427979, 1.46999990940094, 1.0, 1.059999942779541, 1.4199999570846558, 1.2500001192092896, 1.1200000047683716, 0.9499998688697815, 0.9799997806549072, 1.1100000143051147, 1.1400001049041748, 1.1499998569488525, 1.109999656677246, 0.970000147819519, 1.239999771118164, 1.9199998378753662, 2.5399999618530273, 2.119999885559082, 2.169999837875366, 2.4100000858306885, 1.9599997997283936, 1.840000033378601, 1.6899999380111694, 1.540000081062317, 1.549999713897705, 1.75, 1.9199999570846558, 1.8899998664855957, 1.869999885559082, 1.929999828338623, 2.1499998569488525, 2.179999828338623, 1.9300000667572021, 1.779999852180481, 1.760000228881836, 1.7799997329711914, 1.8800002336502075, 1.8799998760223389, 1.5199998617172241, 1.6699997186660767, 1.6500000953674316, 1.6599996089935303, 1.6099998950958252, 1.6399998664855957, 1.5199998617172241, 1.809999704360962, 2.109999656677246, 1.9099998474121094, 2.0199997425079346, 2.0199997425079346, 2.1599998474121094, 2.299999952316284, 2.190000057220459, 2.1399998664855957, 1.9999998807907104, 2.5199997425079346, 1.9200000762939453, 1.9199998378753662, 1.929999828338623, 2.069999933242798, 2.6399998664855957, 2.43999981880188, 1.9099998474121094, 2.6399998664855957, 2.25, 2.6499996185302734, 2.5399999618530273, 2.0899999141693115, 2.75, 2.700000047683716, 2.6499998569488525, 2.9499998092651367, 2.1700000762939453, 2.450000047683716, 2.749999761581421, 2.8299999237060547, 2.169999837875366, 2.120000123977661, 2.109999895095825, 2.309999942779541, 2.2799999713897705, 2.0899999141693115, 2.3399999141693115, 2.2699999809265137, 2.549999713897705, 2.549999952316284, 1.8899998664855957, 2.049999952316284, 1.8599997758865356, 1.6099998950958252, 1.3799998760223389, 1.4000000953674316, 1.6100001335144043, 1.929999828338623, 2.2799997329711914, 1.8199999332427979, 1.8299999237060547, 1.7699997425079346, 1.9500000476837158, 1.9000000953674316, 1.9199998378753662, 1.8499999046325684, 1.9799998998641968, 1.8799999952316284, 1.8599998950958252, 1.7899999618530273, 2.0999999046325684, 1.6999999284744263, 1.8999998569488525, 2.9799997806549072, 3.1399998664855957, 2.8299999237060547, 2.9800000190734863, 3.0199997425079346, 2.669999837875366, 2.7699997425079346, 2.3399999141693115, 2.5, 2.1700000762939453, 2.640000104904175, 2.799999952316284, 2.809999704360962, 2.8199996948242188, 3.5299997329711914, 3.1299996376037598, 2.179999828338623, 2.2899999618530273, 2.2799999713897705, 2.0899999141693115, 2.0799999237060547, 2.0799999237060547, 1.8399999141693115, 1.9999998807907104, 2.5999996662139893, 2.559999704360962, 2.1500000953674316, 2.1499998569488525, 1.929999828338623, 2.0199997425079346, 2.309999704360962, 2.0199999809265137, 1.7099997997283936, 1.7000000476837158, 1.7599997520446777, 1.7099997997283936, 1.4800000190734863, 1.1899998188018799, 1.0499995946884155, 1.010000228881836, 1.0900002717971802, 1.1800001859664917, 1.2899998426437378, 1.2799999713897705, 1.2799997329711914, 1.2099997997283936, 1.3099995851516724, 1.4799998998641968, 1.1899998188018799, 1.0499995946884155, 1.2000001668930054, 1.5499998331069946, 1.2599999904632568, 1.1399997472763062, 1.029999852180481, 0.9700002074241638, 0.8199998140335083, 1.1599997282028198, 1.3599998950958252, 1.5400002002716064, 1.3699997663497925, 1.5899999141693115, 1.5399999618530273, 1.6699997186660767, 1.6600000858306885, 1.7099997997283936, 1.7000000476837158, 1.4699997901916504, 1.4700000286102295, 1.3799999952316284, 1.380000114440918, 1.4600001573562622, 1.749999761581421, 1.7799999713897705, 1.8400001525878906, 1.659999966621399, 1.869999885559082, 2.0999999046325684, 2.1399998664855957, 2.059999942779541, 2.819999933242798, 2.929999589920044, 3.109999895095825, 3.5799999237060547, 3.6399998664855957, 3.7299997806549072, 4.179999828338623, 4.230000019073486, 3.4499995708465576, 3.999999761581421, 3.509999990463257, 3.490000009536743, 3.1499998569488525, 3.129999876022339, 3.7099997997283936, 3.870000123977661, 3.9099998474121094, 3.5199999809265137, 4.539999961853027, 3.7300000190734863, 4.5, 4.199999809265137, 4.039999961853027, 3.359999895095825, 3.0999999046325684, 2.9099998474121094, 3.0399999618530273, 3.5299997329711914, 4.339999675750732, 4.059999465942383, 2.809999942779541, 2.0199997425079346, 2.059999704360962, 1.6399998664855957, 1.6899998188018799, 1.6200001239776611, 1.71999990940094, 1.3799997568130493, 1.53000009059906, 1.75, 2.9099998474121094, 2.629999876022339, 3.7099997997283936, 3.700000047683716, 3.5299997329711914, 3.859999656677246, 3.2699999809265137, 3.069999933242798, 3.059999942779541, 2.6599998474121094, 2.299999952316284, 1.5, 1.179999828338623, 1.4399998188018799, 1.4000000953674316, 1.130000114440918, 1.2299996614456177, 1.440000057220459, 1.540000081062317, 1.5899996757507324, 1.6399998664855957, 1.4999998807907104, 1.399999737739563, 1.4300000667572021, 1.6699998378753662, 1.940000057220459, 2.0399997234344482, 2.1999998092651367, 2.629999876022339, 2.1999998092651367, 2.0799999237060547, 1.959999918937683, 2.319999933242798, 2.359999895095825, 2.0899999141693115, 1.6899999380111694, 1.7600001096725464, 1.8599997758865356, 1.5799999237060547, 1.5900001525878906, 1.459999918937683, 1.4499998092651367, 1.690000295639038, 1.8300000429153442, 1.8299996852874756, 2.0199997425079346, 2.6599998474121094, 3.18999981880188, 3.249999761581421, 3.68999981880188, 3.1600000858306885, 2.9600000381469727, 1.9100000858306885, 1.6499998569488525, 1.5399996042251587, 1.459999680519104, 1.3199998140335083, 1.1999996900558472, 1.2099997997283936, 1.3099995851516724, 1.409999966621399, 1.3599998950958252, 1.220000147819519, 1.5199997425079346, 2.0699996948242188, 2.240000009536743, 2.3899998664855957, 2.119999885559082, 2.1399998664855957, 2.549999713897705, 2.359999895095825, 2.68999981880188, 2.7799997329711914, 2.9099998474121094, 2.7599997520446777, 2.4100000858306885, 3.0099997520446777, 2.239999771118164, 1.7699997425079346, 1.8199999332427979, 2.0799999237060547, 2.4699997901916504, 2.669999837875366, 2.499999761581421, 2.299999952316284, 2.2899999618530273, 1.7000000476837158, 1.5499998331069946, 1.1999999284744263, 0.4999998211860657, 0.9600000381469727, 1.3600000143051147, 1.070000171661377, 1.0600001811981201, 1.409999966621399, 1.4599997997283936, 1.8199998140335083, 2.179999828338623, 2.2799999713897705, 2.2699999809265137, 2.2899997234344482, 2.240000009536743, 2.4699997901916504, 2.379999876022339, 2.549999952316284, 3.0899999141693115, 3.2199997901916504, 3.4599997997283936, 3.9099998474121094, 3.6399998664855957, 3.5999999046325684, 3.8399999141693115, 3.429999828338623, 4.279999732971191, 4.189999580383301, 4.75, 5.210000038146973, 6.110000133514404, 4.929999351501465, 4.529999732971191, 3.5199997425079346, 3.929999828338623, 4.559999942779541, 3.879999876022339, 3.8499999046325684, 4.799999713897705, 4.919999599456787, 4.53000020980835, 6.809999465942383, 6.329999923706055, 5.400000095367432, 3.3999996185302734, 3.239999771118164, 4.059999465942383, 4.239999771118164, 3.5799996852874756, 3.6599998474121094, 2.739999771118164, 2.450000047683716, 2.18999981880188, 2.0099997520446777, 1.9499998092651367, 1.9900000095367432, 2.5799999237060547, 3.379999876022339, 3.299999952316284, 3.2799999713897705, 2.859999895095825, 2.9099998474121094, 2.9499998092651367, 2.9600000381469727, 2.4700000286102295, 3.2699997425079346, 2.880000114440918, 3.3499999046325684, 3.5299999713897705, 3.4099998474121094, 3.2199997901916504, 2.609999895095825, 2.119999885559082, 2.129999876022339, 1.5199999809265137, 1.6599997282028198, 1.779999852180481, 1.8800002336502075, 1.7999998331069946, 1.7400000095367432, 2.0799996852874756, 2.6399998664855957, 3.069999933242798, 2.8999998569488525, 2.8299999237060547, 2.7300000190734863, 3.809999942779541, 3.5999999046325684, 4.139999866485596, 3.809999942779541, 3.299999952316284, 3.9099998474121094, 3.369999885559082, 4.0, 4.179999828338623, 4.639999866485596, 4.529999732971191, 4.229999542236328, 4.369999408721924, 4.349999904632568, 4.400000095367432, 4.189999580383301, 5.039999961853027, 6.119999885559082, 6.199999809265137, 6.099999904632568, 5.449999809265137, 4.460000038146973, 3.549999952316284, 3.7099997997283936, 2.7200000286102295, 2.700000047683716, 3.3299999237060547, 3.059999942779541, 2.1399998664855957, 2.2199997901916504, 2.549999713897705, 2.75, 2.2799999713897705, 2.180000066757202, 2.0900001525878906, 1.9799998998641968, 3.25, 2.859999656677246, 3.179999828338623, 3.299999713897705, 3.3399999141693115, 3.109999895095825, 2.6499998569488525, 2.68999981880188, 2.7799997329711914, 3.1599998474121094, 3.3400001525878906, 3.43999981880188, 3.4499998092651367, 2.8299999237060547, 2.0799999237060547, 4.139999866485596, 4.670000076293945, 6.590000152587891, 7.009999752044678, 6.889999866485596, 6.139999866485596, 6.769999980926514, 7.429999351501465, 7.659999847412109, 7.909999847412109, 8.819999694824219, 7.2699995040893555, 7.829999923706055, 7.799999713897705, 7.679999828338623, 8.380000114440918, 8.260000228881836, 8.630000114440918, 8.40999984741211, 8.399999618530273, 8.079999923706055, 8.079999923706055, 8.069999694824219, 8.469999313354492, 7.520000457763672, 8.25999927520752, 8.480000495910645, 8.529999732971191, 7.710000038146973, 8.25, 8.65999984741211, 8.639999389648438, 9.00999927520752, 9.40000057220459, 9.109999656677246, 9.679999351501465, 9.170000076293945, 8.940000534057617, 8.769999504089355, 9.499999046325684, 9.149999618530273, 9.289999961853027, 9.3100004196167, 9.889999389648438, 9.949999809265137, 9.010000228881836, 10.630000114440918, 10.1899995803833, 9.829999923706055, 9.930000305175781, 9.74000072479248, 9.489999771118164, 9.109999656677246, 9.539999961853027, 9.970000267028809, 10.19999885559082, 10.65999984741211, 10.809999465942383, 10.809999465942383, 10.419999122619629, 10.730000495910645, 10.809999465942383, 12.289999008178711, 11.850000381469727, 11.120000839233398, 12.130000114440918, 12.979999542236328, 13.179999351501465, 13.3100004196167, 13.749999046325684, 13.140000343322754, 12.869998931884766, 12.330000877380371, 12.680000305175781, 12.40999984741211, 13.25, 12.600000381469727, 12.539999008178711, 12.85999870300293, 12.250000953674316, 12.300000190734863, 12.129999160766602, 11.909998893737793, 11.670000076293945, 11.65999984741211, 11.40999984741211, 11.389999389648438, 11.429999351501465, 11.690000534057617, 11.5600004196167, 10.979999542236328, 10.389999389648438, 10.289999008178711, 10.469999313354492, 11.25999927520752, 10.789999961853027, 10.279999732971191, 11.559999465942383, 11.59999942779541, 11.570000648498535, 9.989999771118164, 11.309999465942383, 12.029999732971191, 12.1899995803833, 11.469999313354492, 11.539999008178711, 10.75, 11.550000190734863, 11.379999160766602, 10.84999942779541, 10.350000381469727, 10.420000076293945, 10.0, 9.859999656677246, 9.989999771118164, 9.949999809265137, 9.800000190734863, 9.499999046325684, 9.479999542236328, 9.15999984741211, 9.09999942779541, 9.440000534057617, 9.40999984741211, 9.529999732971191, 9.779999732971191, 9.969999313354492, 10.039999008178711, 10.199999809265137, 9.869999885559082, 9.59000015258789, 9.610000610351562, 10.1899995803833, 10.379999160766602, 9.189998626708984, 8.890000343322754, 9.34999942779541, 8.709999084472656, 9.270000457763672, 9.269999504089355, 9.59999942779541, 10.380000114440918, 9.839999198913574, 8.84000015258789, 8.350000381469727, 8.00999927520752, 9.0, 8.5, 8.390000343322754, 7.939999580383301, 7.87999963760376, 8.369999885559082, 7.75, 7.980000019073486, 7.779999732971191, 7.37999963760376, 7.559999942779541, 8.059999465942383, 7.779999256134033, 6.71999979019165, 7.029999732971191, 7.089999675750732, 6.949999809265137, 6.230000019073486, 6.130000114440918, 5.739999771118164, 5.559999942779541, 5.949999809265137, 5.5, 5.389999866485596, 5.659999847412109, 5.289999961853027, 4.980000019073486, 5.190000057220459, 5.220000267028809, 5.169999599456787, 4.800000190734863, 4.089999675750732, 3.940000057220459, 3.929999828338623, 4.289999961853027, 4.090000152587891, 4.320000171661377, 4.0199995040893555, 3.950000047683716, 3.9699997901916504, 3.7699997425079346, 3.9100000858306885, 4.039999961853027, 4.449999809265137, 4.769999980926514, 5.130000114440918, 4.87999963760376, 5.179999828338623, 5.009999752044678, 5.109999656677246, 5.659999847412109, 5.429999828338623, 6.279999732971191, 5.779999732971191, 5.2099995613098145, 5.480000019073486, 5.159999847412109, 5.349999904632568, 5.449999809265137, 5.369999885559082, 5.25, 5.349999904632568, 5.489999771118164, 5.409999847412109, 5.87999963760376, 5.899999618530273, 5.999999523162842, 6.110000133514404, 5.999999523162842, 6.369999885559082, 6.279999732971191, 7.009999752044678, 7.699999809265137, 7.539999961853027, 7.800000190734863, 7.929999828338623, 7.949999809265137, 8.029999732971191, 8.210000038146973, 8.230000495910645, 7.919999599456787, 7.240000247955322, 6.769999980926514, 6.609999656677246, 6.549999713897705, 6.399999618530273, 6.649999618530273, 6.489999771118164, 6.529999732971191, 6.159999847412109, 6.149999618530273, 5.87999963760376, 6.21999979019165, 6.159999847412109, 6.289999961853027, 6.099999904632568, 5.659999847412109, 5.179999828338623, 5.329999923706055, 5.179999828338623, 5.059999942779541, 4.829999923706055, 4.75, 4.949999809265137, 4.649999618530273, 4.839999675750732, 4.889999866485596, 5.029999732971191, 4.919999599456787, 4.800000190734863, 4.639999866485596, 4.839999675750732, 4.609999656677246, 4.87999963760376, 5.029999732971191, 4.7099995613098145, 4.480000019073486, 4.869999885559082, 4.940000057220459, 4.669999599456787, 4.140000343322754, 3.9799997806549072, 3.5399999618530273, 3.190000057220459, 3.3499999046325684, 3.2899999618530273, 2.5999999046325684, 2.869999647140503, 3.5399999618530273, 3.8899998664855957, 4.139999866485596, 4.150000095367432, 3.8299996852874756, 3.9499998092651367, 4.029999732971191, 3.6999998092651367, 3.4799997806549072, 3.3899998664855957, 3.7699999809265137, 3.6600000858306885, 3.5799999237060547, 3.3299999237060547, 2.859999895095825, 2.4600000381469727, 2.3199996948242188, 2.5299999713897705, 2.259999990463257, 1.8299996852874756, 1.6899996995925903, 1.6200001239776611, 1.6699998378753662, 1.7700001001358032, 1.7300000190734863, 1.8700000047683716, 1.7399998903274536, 1.3799997568130493, 1.6600000858306885, 1.4499998092651367, 1.4200003147125244, 1.2600001096725464, 0.9699997901916504, 0.839999794960022, 0.659999668598175, 0.5699998736381531, 0.5600001811981201, 0.5199999213218689, 0.6200000047683716, 0.7399998903274536, 0.7399997711181641, 0.9299997687339783, 0.729999840259552, 0.739999532699585, 1.149999737739563, 1.5599995851516724, 1.720000147819519, 1.679999828338623, 1.8599998950958252, 2.2799999713897705, 2.0999999046325684, 2.2199997901916504, 2.4699997901916504, 2.369999885559082, 2.359999895095825, 2.2199997901916504, 2.6599998474121094, 2.359999895095825, 2.1999998092651367, 2.2199997901916504, 2.109999895095825, 1.959999918937683, 2.049999952316284, 1.8299996852874756, 1.9199997186660767, 2.1999998092651367, 1.9599997997283936, 2.069999933242798, 2.669999837875366, 2.429999828338623, 2.739999771118164, 3.2100000381469727, 2.68999981880188, 2.0699996948242188, 1.7999999523162842, 1.6699999570846558, 1.1200001239776611, 1.1099998950958252, 1.1400001049041748, 1.4099998474121094, 1.5199998617172241, 1.4499998092651367, 1.700000286102295, 1.6399998664855957, 1.9099998474121094, 1.7299998998641968, 1.6700000762939453, 1.8900001049041748, 1.8799998760223389, 1.96999990940094, 2.049999952316284, 1.8499996662139893, 1.7899999618530273, 1.9700000286102295, 1.8100000619888306, 1.959999680519104, 1.6400001049041748, 1.3499999046325684, 1.1099998950958252, 1.03000009059906, 0.8300002217292786, 1.0999999046325684, 1.0499999523162842, 1.2900002002716064, 1.2200000286102295, 1.0099997520446777, 0.9800002574920654, 1.0099999904632568, 0.7100002765655518, 0.5, 0.6200000047683716, 0.619999885559082, 0.6299998760223389, 1.1800000667572021, 1.4099998474121094, 0.9499998092651367, 0.5399998426437378, 0.5999999642372131, 0.6999999284744263, 0.8100003004074097, 0.9999999403953552, 1.1100000143051147, 1.28000009059906, 1.4399996995925903, 1.3600000143051147, 1.4500001668930054, 1.440000295639038, 1.28000009059906, 0.9199997186660767, 0.5900000333786011, 1.070000171661377, 1.1800001859664917, 0.7099997997283936, 0.5500000715255737, 0.2699997127056122, 0.26999998092651367, 0.4399999976158142, 0.7799996137619019, 0.6699997186660767, 0.6200000643730164, 0.779999852180481, 0.8299997448921204, 0.9599999189376831, 1.0800000429153442, 1.3599998950958252, 1.630000114440918, 1.7399996519088745, 1.9099997282028198, 1.8799998760223389, 1.71999990940094, 2.239999771118164, 2.0899996757507324, 2.569999933242798, 3.2899999618530273, 1.9299999475479126, 1.4699997901916504, 1.4300000667572021, 1.2199997901916504, 1.0699998140335083, 0.9800001978874207, 1.190000057220459, 2.109999656677246, 2.369999885559082, 2.68999981880188, 2.569999933242798, 1.7899999618530273, 1.6100000143051147, 1.4799998998641968, 1.499999761581421, 1.2899997234344482, 1.1899999380111694, 1.239999532699585, 1.299999713897705, 1.3299996852874756, 1.1699999570846558, 1.2799996137619019, 1.3599997758865356, 1.130000114440918, 1.0099996328353882, 0.850000262260437, 0.7299998998641968, 0.6499995589256287, 0.6500000953674316, 0.44000008702278137, 0.6399995684623718, 0.6699998378753662, 0.8200000524520874, 0.7799996733665466, 0.6699997186660767, 0.9900000691413879, 0.9899997711181641, 1.3299998044967651, 1.3599998950958252, 1.220000147819519, 1.2899998426437378, 1.159999966621399, 1.3299998044967651, 1.2899999618530273, 1.1799999475479126, 1.0499998331069946, 1.3500001430511475, 1.159999966621399, 0.979999840259552, 1.3100000619888306, 1.4499999284744263, 1.4100003242492676, 1.3999998569488525, 1.3900001049041748, 1.3999998569488525, 1.290000081062317, 1.3299999237060547, 1.2999999523162842, 1.359999656677246, 1.5900001525878906, 1.5799999237060547, 1.6100001335144043, 1.5399999618530273, 1.4499996900558472, 1.4100003242492676, 1.3299998044967651, 1.3799998760223389, 1.4600001573562622, 1.5199997425079346, 1.549999713897705, 1.3799999952316284, 1.3900001049041748, 1.2699998617172241, 1.2799999713897705, 1.3799997568130493, 1.1400001049041748, 1.1699998378753662, 1.0499995946884155, 1.0200002193450928, 1.1100000143051147, 1.2600001096725464, 1.2199997901916504, 1.249999761581421, 1.7799999713897705, 2.9800000190734863, 2.809999704360962, 1.9199997186660767, 1.529999852180481, 1.524999976158142, 1.5199998617172241, 1.559999704360962, 1.6400002241134644, 1.459999918937683, 1.3199998140335083, 1.4799996614456177, 1.339999794960022, 1.2800002098083496, 1.489999771118164, 1.5499999523162842, 1.6999999284744263, 1.8899998664855957, 1.96999990940094, 2.6700000762939453, 2.999999761581421, 3.049999713897705, 3.2300000190734863, 2.919999837875366, 2.739999771118164, 2.6700000762939453, 2.9799997806549072, 3.0299997329711914, 3.4799997806549072, 3.109999895095825, 2.759999990463257, 2.490000009536743, 2.739999771118164, 2.819999933242798, 3.0999996662139893, 2.8899998664855957, 2.629999876022339, 2.5299999713897705, 2.879999876022339, 2.739999771118164, 2.0899999141693115, 1.9799998998641968, 1.840000033378601, 1.6999999284744263, 1.6099997758865356, 1.619999885559082, 1.4399999380111694, 1.3200000524520874, 1.309999704360962, 1.369999885559082, 1.2699998617172241, 1.5399999618530273, 1.5899996757507324, 1.4299999475479126, 1.2499998807907104, 1.2699999809265137, 1.2000000476837158, 1.2699998617172241, 1.2400000095367432, 1.489999771118164, 1.7899999618530273, 1.5899999141693115, 1.5299999713897705, 0.8899999856948853, 0.42999985814094543, 0.679999828338623, 1.0100003480911255, 1.010000228881836, 1.0900002717971802, 1.1000001430511475, 1.2399998903274536, 1.089999794960022, 0.9900001883506775, 1.0199997425079346, 0.7100000381469727, 0.5100000500679016, 0.3699997663497925, 0.4299998879432678, 0.7599998712539673, 0.7099997401237488, 0.9300000667572021, 0.8899998068809509, 1.1499998569488525, 1.3499996662139893, 1.4799998998641968, 1.649999737739563, 1.7399996519088745, 2.0299997329711914, 2.179999828338623, 2.5500001907348633, 2.4099998474121094, 2.68999981880188, 2.0199997425079346, 2.8399996757507324, 3.4800000190734863, 3.5699996948242188, 3.5999996662139893, 3.989999771118164, 3.8399996757507324, 3.739999771118164, 4.109999656677246, 4.34999942779541, 4.529999732971191, 4.279999732971191, 3.8199996948242188, 3.619999647140503, 4.099999904632568, 4.859999656677246, 4.2099995613098145, 4.710000038146973, 4.53000020980835, 4.759999752044678, 4.169999599456787, 4.059999942779541, 4.099999904632568, 3.859999895095825, 4.069999694824219, 3.439999580383301, 3.3899998664855957, 3.559999942779541, 3.450000047683716, 3.619999885559082, 3.919999837875366, 3.559999942779541, 3.4700000286102295, 3.1499998569488525, 2.7899999618530273, 2.2199997901916504, 2.1399998664855957, 1.6399998664855957, 1.279999852180481, 1.2899997234344482, 1.3799999952316284, 1.3400001525878906, 1.2900002002716064, 1.1200000047683716, 1.1699998378753662, 1.1599996089935303, 1.0399998426437378, 0.9799999594688416, 1.0800000429153442, 0.9899999499320984, 1.0199997425079346, 0.9799999594688416, 1.2000000476837158, 1.179999828338623, 1.4799997806549072, 1.6399997472763062, 1.5199998617172241, 1.5799996852874756, 1.660000205039978, 1.619999885559082, 1.6999999284744263, 1.7699998617172241, 1.6899999380111694, 1.4800000190734863, 1.489999771118164, 1.5600000619888306, 1.5900001525878906, 1.5199999809265137, 1.0399997234344482, 0.6999999284744263, 0.8700003027915955, 0.8399999141693115, 0.7999996542930603, 0.8399997353553772, 0.8399996757507324, 0.9199996590614319, 1.1500000953674316, 1.2599996328353882, 1.1099997758865356, 0.9400001168251038, 1.0100001096725464, 0.9000002145767212, 1.380000114440918, 1.4200000762939453, 1.1500000953674316, 1.2099995613098145, 1.1599996089935303, 0.979999840259552, 1.100000023841858, 1.2299998998641968, 1.0800000429153442, 1.1299998760223389, 1.3199996948242188, 1.5699996948242188, 1.6899999380111694, 1.8300000429153442, 1.9099997282028198, 1.8299998044967651, 1.8199996948242188, 1.7899999618530273, 1.7599999904632568, 1.739999771118164, 1.679999828338623, 1.5099998712539673, 1.4600000381469727, 1.4199998378753662, 1.1600000858306885, 1.0799998044967651, 1.1799999475479126, 1.3099998235702515, 1.3399999141693115, 1.380000114440918, 1.1400001049041748, 0.7199998497962952, 0.5799998044967651, 0.5299999117851257, 0.5299997329711914, 1.0199997425079346, 1.3799999952316284, 1.4300000667572021, 1.369999885559082, 1.429999828338623, 1.3999998569488525, 1.470000147819519, 1.5299999713897705, 1.309999942779541, 1.1399999856948853, 1.029999852180481, 0.9300002455711365, 0.9599997997283936, 1.090000033378601, 1.1700001955032349, 1.1599996089935303, 1.4099998474121094, 1.619999885559082, 1.809999942779541, 2.0699996948242188, 2.319999933242798, 2.179999828338623, 2.240000009536743, 2.4099998474121094, 2.359999895095825, 2.6499998569488525, 1.9699997901916504, 2.690000057220459, 2.0899999141693115, 2.7100000381469727, 2.429999828338623, 3.2599997520446777, 3.239999771118164, 3.129999876022339, 3.6399998664855957, 3.5199999809265137, 3.509999990463257, 3.3399999141693115, 3.679999828338623, 3.5399997234344482, 3.629999876022339, 3.049999952316284, 3.359999895095825, 3.43999981880188, 3.2099997997283936, 3.2599997520446777, 3.68999981880188, 4.71999979019165, 3.429999828338623, 3.059999942779541, 4.079999923706055, 4.639999866485596, 4.789999961853027, 4.659999847412109, 4.019999980926514, 3.6600000858306885, 4.399999618530273, 3.9499995708465576, 3.4699997901916504, 3.0699996948242188, 1.9399998188018799, 1.8099998235702515, 1.799999713897705, 1.5299999713897705, 1.6899999380111694, 1.6400001049041748, 1.5999999046325684, 1.459999918937683, 1.2999998331069946, 1.299999713897705, 1.2199996709823608, 0.9999997615814209, 0.8100000023841858, 0.9099999666213989, 0.9099998474121094, 0.979999840259552, 1.0600000619888306, 1.3899999856948853, 1.21999990940094, 1.0699998140335083, 0.9900001883506775, 0.8799997568130493, 0.819999635219574, 0.8199996948242188, 1.0899996757507324, 1.1400001049041748, 1.0799999237060547, 1.0699999332427979, 0.8800001740455627, 0.8399996161460876, 0.8299996852874756, 0.6599999070167542, 0.43999984860420227, 0.4699995815753937, 0.7799997925758362, 1.5199997425079346, 1.8699997663497925, 2.2199997901916504, 2.18999981880188, 1.9199998378753662, 1.7499998807907104, 2.059999942779541, 1.659999966621399, 1.3899998664855957, 1.119999885559082, 1.119999885559082, 1.2999999523162842, 1.459999680519104, 1.749999761581421, 1.5199999809265137, 1.2599997520446777, 1.1699997186660767, 0.9899995923042297, 0.8099997639656067, 0.9999999403953552, 1.2200000286102295, 1.1599998474121094, 1.279999852180481, 1.489999771118164, 1.4500000476837158, 1.290000319480896, 1.459999918937683, 1.489999771118164, 1.4800000190734863, 1.6099997758865356, 1.8799998760223389, 2.18999981880188, 2.859999895095825, 2.6999998092651367, 1.999999761581421, 1.839999794960022, 1.8199999332427979, 1.75, 1.7300000190734863, 1.7599999904632568, 1.649999737739563, 1.5899996757507324, 2.0199999809265137, 1.5299997329711914, 1.4800000190734863, 1.4199998378753662, 1.5600000619888306, 1.3900002241134644, 1.4399998188018799, 1.0500000715255737, 1.1300002336502075, 1.2499996423721313, 1.2799999713897705, 1.249999761581421, 1.2100000381469727, 1.2599995136260986, 1.1799997091293335, 1.0399998426437378, 1.0999999046325684, 1.2599998712539673, 1.2099997997283936, 0.8199995756149292, 0.5199997425079346, 0.4999999701976776, 0.4300000071525574, 0.7399998307228088, 0.7599997520446777, 0.8699997663497925, 0.9899998903274536, 1.3299998044967651, 1.7899999618530273, 1.9900000095367432, 2.0, 2.1999998092651367, 2.2799997329711914, 3.009999990463257, 3.1999998092651367, 3.239999771118164, 3.7799997329711914, 3.549999713897705, 3.3799996376037598, 3.129999876022339, 3.299999952316284, 3.379999876022339, 3.319999933242798, 3.869999885559082, 3.759999990463257, 3.309999704360962, 3.5299999713897705, 3.3299996852874756, 2.9600000381469727, 3.309999942779541, 3.2200000286102295, 3.5399997234344482, 3.9499998092651367, 3.249999761581421, 2.8899998664855957, 3.2899999618530273, 2.6599998474121094, 1.9599997997283936, 1.6100000143051147, 1.7699998617172241, 1.850000023841858, 1.7899999618530273, 1.7200000286102295, 1.8999998569488525, 1.9399998188018799, 2.309999942779541, 2.1399998664855957, 1.6099998950958252, 1.7699998617172241, 2.179999828338623, 2.5500001907348633, 2.8499999046325684, 2.679999828338623, 2.2299997806549072, 2.5399997234344482, 2.299999952316284, 1.7000000476837158, 1.4499998092651367, 1.6600003242492676, 1.429999828338623, 1.339999794960022, 1.1500002145767212, 1.1299996376037598, 1.1599996089935303, 1.0999999046325684, 1.059999942779541, 0.8999999761581421, 0.8700001239776611, 0.7799999117851257, 0.7699997425079346, 0.7899994850158691, 0.8499999642372131, 0.919999897480011, 0.8700000643730164, 0.9799998998641968, 0.9200000166893005, 0.9300000667572021, 0.979999840259552, 1.100000023841858, 1.0899999141693115, 1.0200002193450928, 1.0, 1.059999942779541, 0.8299999237060547, 0.9299999475479126, 0.8999998569488525, 0.9700000882148743, 0.9899997711181641, 1.149999737739563, 1.1499996185302734, 1.2999995946884155, 1.4499996900558472, 1.440000295639038, 1.2700001001358032, 1.2100000381469727, 1.2199995517730713, 1.1999998092651367, 1.1199997663497925, 1.1099998950958252, 0.9800001382827759, 1.1100000143051147, 1.1700000762939453, 1.2999995946884155, 1.2199996709823608, 1.0699998140335083, 1.1400002241134644, 1.0899999141693115, 1.070000171661377, 1.2100001573562622, 1.2299995422363281, 1.2400000095367432, 1.339999794960022, 1.3600001335144043, 1.3400001525878906, 1.1800001859664917, 1.239999771118164, 1.2699997425079346, 1.2899999618530273, 1.2999999523162842, 1.359999656677246, 1.4100000858306885, 1.4799998998641968, 1.5999997854232788, 1.8899998664855957, 1.9199998378753662, 1.6899998188018799, 1.690000057220459, 1.630000114440918, 1.3999996185302734, 1.3300001621246338, 1.1999999284744263, 1.3099998235702515, 1.4199999570846558, 1.6200001239776611, 1.6299998760223389, 1.5799996852874756, 1.3500001430511475, 1.3799998760223389, 1.0500000715255737, 1.1000001430511475, 1.21999990940094, 1.0499998331069946, 1.1800001859664917, 1.3199998140335083, 1.2799997329711914, 1.5099997520446777, 1.5499999523162842, 1.899999976158142, 1.929999828338623, 1.989999771118164, 2.309999942779541, 2.5199999809265137, 2.379999876022339, 2.1399998664855957, 2.4099998474121094, 2.2799997329711914, 2.75, 2.799999952316284, 2.3999996185302734, 3.069999933242798, 3.0399999618530273, 3.1499996185302734, 3.7099997997283936, 4.28000020980835, 3.859999656677246, 3.7099997997283936, 4.349999904632568, 4.360000133514404, 4.509999752044678, 4.789999961853027, 4.820000171661377, 4.039999961853027, 3.9700000286102295, 3.4499998092651367, 3.68999981880188, 4.059999942779541, 3.309999942779541, 3.179999828338623, 3.379999876022339, 3.429999828338623, 2.929999828338623, 2.4699997901916504, 2.8499999046325684, 3.25, 3.2099997997283936, 3.2599997520446777, 3.5899996757507324, 4.279999732971191, 3.2899997234344482, 3.6499998569488525, 3.4699997901916504, 3.3999998569488525, 3.169999837875366, 3.3399999141693115, 3.4600000381469727, 2.68999981880188, 2.129999876022339, 1.7899998426437378, 1.6200000047683716, 1.5199998617172241, 1.6599997282028198, 1.4899998903274536, 1.8600000143051147, 1.9299999475479126, 1.9499998092651367, 1.8600000143051147, 1.9899998903274536, 2.240000009536743, 2.609999656677246, 2.559999942779541, 2.25, 2.0899996757507324, 2.3299999237060547, 2.059999942779541, 1.8700000047683716, 1.71999990940094, 1.6599998474121094, 1.4399998188018799, 1.380000114440918, 1.3700001239776611, 1.3799998760223389, 1.570000171661377, 1.8799998760223389, 1.929999828338623, 1.9699997901916504, 1.8000000715255737, 1.6799999475479126, 1.6099998950958252, 1.6599998474121094, 1.429999828338623, 1.3599998950958252, 1.5000001192092896, 1.4799997806549072, 1.3899997472763062, 1.6999998092651367, 1.749999761581421, 1.7699999809265137, 1.8799999952316284, 2.0199999809265137, 1.9399996995925903, 1.8299998044967651, 1.869999647140503, 2.059999942779541, 2.2799999713897705, 2.4099998474121094, 2.069999933242798, 2.299999952316284, 2.299999952316284, 1.9399999380111694, 1.9699997901916504, 1.9700000286102295, 1.840000033378601, 1.6399998664855957, 1.5699999332427979, 1.6399999856948853, 1.46999990940094, 1.4200000762939453, 1.440000057220459, 1.4900000095367432, 1.3899999856948853, 1.2899998426437378, 1.3499999046325684, 1.4499999284744263, 1.5800002813339233, 1.7400001287460327, 1.7799997329711914, 1.8400001525878906, 1.9799998998641968, 2.1100001335144043, 1.9899998903274536, 2.1700000762939453, 2.2300000190734863, 2.489999771118164, 2.359999656677246, 2.069999933242798, 1.8399999141693115, 1.809999942779541, 1.7899997234344482, 1.7799999713897705, 1.850000262260437, 1.869999885559082, 1.6999999284744263, 1.6499998569488525, 1.7299996614456177, 1.3300000429153442, 0.8999999165534973, 0.8200001120567322, 1.1399996280670166, 0.8799998760223389, 1.0099996328353882, 0.7900002002716064, 1.2899999618530273, 1.5, 1.3299998044967651, 1.4199999570846558, 1.4500000476837158, 1.5200003385543823, 1.799999713897705, 1.71999990940094, 1.8799997568130493, 2.489999771118164, 2.0099997520446777, 2.2799997329711914, 2.5399999618530273, 1.8299999237060547, 2.0799996852874756, 2.2899999618530273, 2.069999933242798, 2.3499999046325684, 2.3999998569488525, 2.299999952316284, 2.3899998664855957, 2.319999933242798, 2.3499999046325684, 2.4800000190734863, 2.7599997520446777, 3.0399999618530273, 3.3299996852874756, 3.18999981880188, 2.799999713897705, 3.4499998092651367, 3.2199997901916504, 4.199999809265137, 3.559999942779541, 3.440000057220459, 3.7199997901916504, 5.339999675750732, 6.34999942779541, 5.630000114440918, 5.71999979019165, 4.939999580383301, 4.029999732971191, 4.299999713897705, 3.580000162124634, 4.039999961853027, 3.4200000762939453, 2.7299997806549072, 2.759999990463257, 1.9299999475479126, 1.8499997854232788, 2.069999933242798, 2.1999998092651367, 2.2599997520446777, 2.2099997997283936, 2.629999876022339, 2.7799999713897705, 3.630000114440918, 3.429999828338623, 3.5199997425079346, 3.049999952316284, 2.059999942779541, 2.129999876022339, 2.4099998474121094, 1.8399999141693115, 1.7699999809265137, 1.75, 1.5299999713897705, 1.2799999713897705, 1.1999996900558472, 1.0799998044967651, 0.9599999189376831, 0.9800000190734863, 1.0500000715255737, 1.3000001907348633, 1.5299997329711914, 1.5699999332427979, 1.3499999046325684, 1.1499998569488525, 0.9499996304512024, 0.7599998116493225, 0.8599997758865356, 0.7799996733665466, 1.0799996852874756, 1.159999966621399, 1.029999852180481, 1.1500002145767212, 1.2899996042251587, 1.3499999046325684, 1.5799999237060547, 1.7800002098083496, 1.9300001859664917, 1.839999794960022, 1.909999966621399, 2.3499999046325684, 2.419999837875366, 1.8899998664855957, 1.7299998998641968, 1.4900000095367432, 1.1399999856948853, 1.0799999237060547, 0.9799999594688416, 0.9700000286102295, 0.7499997615814209, 0.8399995565414429, 1.0899996757507324, 1.2700002193450928, 1.2699999809265137, 1.0199999809265137, 0.8799999952316284, 0.819999635219574, 0.7699996829032898, 0.5599994659423828, 1.1099998950958252, 1.7400001287460327, 1.739999771118164, 1.5799998044967651, 1.4200001955032349, 1.3200000524520874, 0.9799996614456177, 0.9200000166893005, 1.1000001430511475, 0.8999999165534973, 1.2200000286102295, 1.429999828338623, 1.8599998950958252, 1.8999998569488525, 1.4899998903274536, 1.4300000667572021, 1.369999885559082, 1.1299998760223389, 1.0399996042251587, 1.0399999618530273, 0.8999999761581421, 0.7900000810623169, 1.1799999475479126, 1.429999828338623, 1.0699998140335083, 0.9900001883506775, 0.7099997997283936, 0.7800000309944153, 0.9199997186660767, 0.9100000858306885, 1.0899999141693115, 1.2800002098083496, 0.9699997901916504, 1.0799998044967651, 1.119999885559082, 1.1099998950958252, 1.0000001192092896, 1.4300000667572021, 1.6699998378753662, 2.0199999809265137, 2.0099997520446777, 2.6399998664855957, 2.049999952316284, 2.419999599456787, 2.4499998092651367, 2.109999895095825, 2.5199999809265137, 2.8299999237060547, 3.2100000381469727, 3.4499998092651367, 2.8299999237060547, 2.8899998664855957, 3.359999895095825, 3.0199999809265137, 2.93999981880188, 3.009999990463257, 3.3399996757507324, 3.68999981880188, 3.2800002098083496, 3.929999828338623, 4.369999885559082, 4.789999961853027, 5.239999771118164, 5.639999866485596, 6.069999694824219, 6.399999618530273, 6.87999963760376, 5.479999542236328, 4.389999866485596, 4.019999980926514, 4.139999866485596, 5.279999732971191, 4.849999904632568, 4.190000057220459, 4.860000133514404, 6.62999963760376, 7.190000057220459, 7.779999732971191, 8.799999237060547, 8.709999084472656, 8.0600004196167, 7.84999942779541, 7.900000095367432, 9.179999351501465, 10.039999961853027, 10.170000076293945, 9.819999694824219, 9.75, 10.4399995803833, 10.580000877380371, 10.470000267028809, 9.369998931884766, 5.849999904632568, 6.71999979019165, 7.889999866485596, 6.460000038146973, 7.039999961853027, 7.269999980926514, 8.399999618530273, 8.5, 9.079999923706055, 8.319999694824219, 8.920000076293945, 10.229999542236328, 7.729999542236328, 7.779999732971191, 9.199999809265137, 10.729999542236328, 11.959999084472656, 10.949999809265137, 12.079999923706055, 11.930000305175781, 11.170000076293945, 10.75, 10.6899995803833, 9.739999771118164, 9.4399995803833, 9.59999942779541, 9.200000762939453, 8.84000015258789, 7.820000171661377, 8.809999465942383, 8.739999771118164, 8.079999923706055, 8.0, 6.929999828338623, 7.069999694824219, 5.96999979019165, 4.859999656677246, 5.439999580383301, 4.809999942779541, 5.179999828338623, 5.169999599456787, 4.269999980926514, 6.350000381469727, 5.840000152587891, 6.369999885559082, 5.619999885559082, 5.980000019073486, 6.269999980926514, 5.010000228881836, 4.659999847412109, 3.879999876022339, 4.170000076293945, 7.460000038146973, 8.380000114440918, 8.199999809265137, 7.689999580383301, 7.559999465942383, 6.679999351501465, 7.449999809265137, 7.269999980926514, 7.179999828338623, 6.829999923706055, 6.429999828338623, 5.87999963760376, 5.3299994468688965, 5.779999732971191, 4.71999979019165, 5.029999732971191, 4.599999904632568, 4.139999866485596, 3.8499999046325684, 2.8899998664855957, 1.4499998092651367, 1.9900002479553223, 2.6500000953674316, 3.2899999618530273, 3.299999952316284, 2.879999876022339, 2.7299997806549072, 2.430000066757202, 2.869999885559082, 3.0, 2.9799997806549072, 3.0799996852874756, 3.9099998474121094, 3.609999895095825, 4.539999961853027, 5.139999866485596, 4.5, 4.599999904632568, 5.25, 4.900000095367432, 4.5199995040893555, 4.199999809265137, 4.049999713897705, 3.7699997425079346, 3.3600001335144043, 3.799999952316284, 3.740000009536743, 4.029999732971191, 4.349999904632568, 4.139999866485596, 3.8999998569488525, 3.9599997997283936, 3.5099997520446777, 3.319999933242798, 2.5299999713897705, 2.799999952316284, 2.249999761581421, 1.839999794960022, 2.2699999809265137, 2.249999761581421, 1.8699997663497925, 1.6099998950958252, 1.6799999475479126, 1.5399998426437378, 1.549999713897705, 1.409999966621399, 1.2699998617172241, 1.4600000381469727, 1.5999997854232788, 2.419999837875366, 1.9399998188018799, 1.4599997997283936, 1.1499998569488525, 1.1299996376037598, 0.8899996280670166, 0.8999998569488525, 0.9300000667572021, 0.8199998140335083, 0.8499996662139893, 0.8099998831748962, 0.8399999141693115, 0.8399996757507324, 0.9299997091293335, 0.9199998378753662, 1.0600000619888306, 0.9899999499320984, 0.7299997806549072, 0.4399995505809784, 0.8699995875358582, 1.3499999046325684, 1.5499999523162842, 1.2799999713897705, 1.6099997758865356, 1.5199998617172241, 1.1799997091293335, 1.1299998760223389, 0.9299996495246887, 0.5799998044967651, 0.6299999356269836, 0.9100000858306885, 0.8099998831748962, 0.85999995470047, 1.209999680519104, 1.5499995946884155, 1.7400000095367432, 2.5899996757507324, 2.549999952316284, 2.0199999809265137, 2.5099997520446777, 3.490000009536743, 3.489999771118164, 3.2099997997283936, 3.239999771118164, 3.359999656677246, 3.5299999713897705, 4.009999752044678, 4.049999713897705, 3.799999713897705, 3.200000047683716, 3.1399998664855957, 2.5799999237060547, 1.709999918937683, 1.4900000095367432, 1.2599999904632568, 1.3199996948242188, 1.1799997091293335, 1.3299998044967651, 1.659999966621399, 1.279999852180481, 1.059999704360962, 1.0199999809265137, 1.559999942779541, 1.720000147819519, 1.8999998569488525, 1.9199998378753662, 1.7699998617172241, 1.7599999904632568, 2.1999998092651367, 2.609999656677246, 2.5999999046325684, 2.2799997329711914, 2.7200000286102295, 3.7699999809265137, 3.75, 3.8399999141693115, 3.8399996757507324, 4.149999618530273, 3.8499996662139893, 3.6499998569488525, 2.9499998092651367, 2.3600001335144043, 2.4800000190734863, 1.7299997806549072, 1.7300000190734863, 1.590000033378601, 1.3199999332427979, 1.1299997568130493, 1.3399996757507324, 1.3500001430511475, 1.5499999523162842, 1.5899999141693115, 1.9499999284744263, 2.6600000858306885, 2.4699997901916504, 1.8499997854232788, 1.5299999713897705, 1.7899999618530273, 1.8700000047683716, 1.9099998474121094, 1.869999885559082, 1.8399999141693115, 1.9499999284744263, 1.8100000619888306, 1.7599997520446777, 2.0699996948242188, 2.2300000190734863, 2.2299997806549072, 2.2699997425079346, 2.3799996376037598, 2.3399999141693115, 2.5, 2.7100000381469727, 2.809999704360962, 3.0299997329711914, 2.5999996662139893, 2.7799997329711914, 2.549999952316284, 2.009999990463257, 2.2599997520446777, 2.3299996852874756, 2.319999933242798, 2.379999876022339, 2.7199997901916504, 3.2200000286102295, 3.169999837875366, 2.8399999141693115, 2.9800000190734863, 3.429999828338623, 3.109999895095825, 2.8899998664855957, 2.7099997997283936, 2.5699996948242188, 2.8499999046325684, 2.759999990463257, 3.2799999713897705, 2.299999952316284, 2.049999952316284, 1.749999761581421, 1.5199999809265137, 1.4499998092651367, 1.510000228881836, 1.559999942779541, 1.4900002479553223, 1.590000033378601, 1.709999918937683, 1.75, 1.7899999618530273, 1.7200000286102295, 1.8499997854232788, 1.8599998950958252, 1.6399998664855957, 1.529999852180481, 2.0999999046325684, 2.379999876022339, 2.3399999141693115, 2.059999942779541, 2.0199999809265137, 1.5699996948242188, 1.459999918937683, 1.3999998569488525, 1.2600001096725464, 0.8599997758865356, 0.519999623298645, 0.32999998331069946, 0.19999992847442627, 0.17999981343746185, 0.18999983370304108, 0.31000006198883057, 0.35999995470046997, 0.2999996542930603, 0.1800002008676529, 0.2299998253583908, 0.24000002443790436, 0.27000024914741516, 0.3699999749660492, 0.3899998962879181, 0.39999985694885254, 0.3499996066093445, 0.5199999213218689, 0.7799999713897705, 0.7499997615814209, 0.7299995422363281, 1.8499995470046997, 1.5699999332427979, 1.5999999046325684, 2.0399999618530273, 2.3999996185302734, 3.4499998092651367, 3.169999837875366, 2.5099997520446777, 2.069999933242798, 1.7999999523162842, 1.8899999856948853, 2.2799997329711914, 2.5899999141693115, 2.8299999237060547, 2.179999828338623, 2.430000066757202, 2.6499998569488525, 2.5099997520446777, 2.7100000381469727, 1.9199998378753662, 1.4099998474121094, 1.1899998188018799, 1.239999532699585, 0.9199997782707214, 0.7700001001358032, 0.9699994921684265, 0.8199998140335083, 0.8699997067451477, 0.7199999094009399, 0.7599998116493225, 0.6199997663497925, 0.7999998927116394, 1.049999713897705, 1.2800002098083496, 1.3199996948242188, 1.4199997186660767, 1.340000033378601, 1.3000001907348633, 1.049999713897705, 1.0800001621246338, 0.869999885559082, 0.9899998903274536, 1.3299998044967651, 1.6499998569488525, 1.2999995946884155, 1.0399997234344482, 1.0199999809265137, 1.1399999856948853, 1.2699998617172241, 1.3700000047683716, 1.279999852180481, 1.059999704360962, 1.3199999332427979, 1.5199997425079346, 1.9799997806549072, 1.9900000095367432, 2.2799999713897705, 1.5, 1.6399997472763062, 2.2199997901916504, 1.619999885559082, 1.3999998569488525, 1.4800001382827759, 1.3799997568130493, 1.0900001525878906, 0.9400001764297485, 0.7300000190734863, 0.5099995136260986, 0.2799997627735138, 0.5400002002716064, 0.6699999570846558, 0.9000000953674316, 1.0600000619888306, 1.3799998760223389, 1.7000000476837158, 1.6899998188018799, 1.840000033378601, 1.8799998760223389, 2.5299997329711914, 2.809999942779541, 2.239999771118164, 2.249999761581421, 2.369999885559082, 2.43999981880188, 2.6999998092651367, 2.869999885559082, 3.169999837875366, 3.2899999618530273, 3.3899998664855957, 2.859999895095825, 3.2199997901916504, 3.379999876022339, 3.2699999809265137, 3.440000057220459, 3.2299997806549072, 3.7199997901916504, 3.2799997329711914, 3.490000009536743, 4.009999752044678, 3.6299996376037598, 3.419999837875366, 3.2899999618530273, 3.450000047683716, 3.739999771118164, 3.179999828338623, 3.3299999237060547, 2.990000009536743, 3.4599997997283936, 4.21999979019165, 3.7799997329711914, 3.5699996948242188, 3.6299996376037598, 4.759999752044678, 4.599999904632568, 4.710000038146973, 4.949999809265137, 5.489999771118164, 5.149999618530273, 4.589999675750732, 3.299999713897705, 2.490000009536743, 2.249999761581421, 1.989999771118164, 1.7300000190734863, 1.8200000524520874, 1.5799999237060547, 1.2900002002716064, 1.2599999904632568, 1.4699997901916504, 1.7200000286102295, 1.6299997568130493, 1.619999647140503, 1.5099998712539673, 1.4199999570846558, 1.3900001049041748, 1.459999918937683, 1.3099998235702515, 1.3799999952316284, 1.320000171661377, 1.249999761581421, 1.0199999809265137, 0.9200000166893005, 0.8600000739097595, 0.7799996733665466, 0.9899997711181641, 1.1199997663497925, 1.209999918937683, 1.5099995136260986, 1.7899999618530273, 2.359999895095825, 2.1599998474121094, 2.43999981880188, 2.6399998664855957, 1.779999852180481, 2.010000228881836, 3.059999465942383, 2.0199999809265137, 2.1599998474121094, 3.2299997806549072, 3.169999837875366, 2.679999828338623, 2.9699997901916504, 3.2699999809265137, 3.559999942779541, 3.7899999618530273, 2.5399999618530273, 3.179999828338623, 2.9799997806549072, 3.5299997329711914, 2.859999656677246, 2.859999895095825, 2.5799999237060547, 1.9199998378753662, 2.1399998664855957, 1.8399999141693115, 1.8199999332427979, 1.619999885559082, 1.4499999284744263, 1.5700002908706665, 1.5899999141693115, 1.7299998998641968, 1.6200000047683716, 1.6499998569488525, 1.7399996519088745, 1.989999771118164, 2.059999942779541, 2.5899999141693115, 1.8999998569488525, 2.669999837875366, 3.939999580383301, 4.049999713897705, 3.4099998474121094, 3.6599998474121094, 3.7199997901916504, 3.6499998569488525, 3.669999837875366, 3.2199997901916504, 2.9699997901916504, 2.6500000953674316, 1.989999771118164, 1.8100000619888306, 1.739999771118164, 1.8499997854232788, 1.71999990940094, 1.6499998569488525, 1.6499996185302734, 2.2699995040893555, 2.8199996948242188, 3.049999713897705, 2.879999876022339, 3.7699999809265137, 3.9800000190734863, 4.150000095367432, 4.619999408721924, 5.319999694824219, 6.289999485015869, 6.650000095367432, 6.909999847412109, 8.460000038146973, 9.09000015258789, 8.390000343322754, 9.059999465942383, 9.15999984741211, 8.880000114440918, 8.770000457763672, 8.949999809265137, 8.09000015258789, 8.40000057220459, 6.979999542236328, 7.499999523162842, 6.960000038146973, 7.369999885559082, 8.119999885559082, 7.880000114440918, 8.350000381469727, 7.799999237060547, 8.949999809265137, 7.130000114440918, 7.099999904632568, 7.0, 6.309999942779541, 6.440000057220459, 6.259999752044678, 7.039999961853027, 6.179999828338623, 6.819999694824219, 5.989999771118164, 7.099999904632568, 6.139999866485596, 5.440000057220459, 5.240000247955322, 5.059999942779541, 5.170000076293945, 4.740000247955322, 4.799999713897705, 2.7099997997283936, 2.7799997329711914, 3.0299999713897705, 3.18999981880188, 2.1599998474121094, 1.3499999046325684, 1.459999918937683, 1.5199997425079346, 1.5999997854232788, 1.3899998664855957, 1.1699998378753662, 0.7799996137619019, 1.1899996995925903, 1.429999589920044, 1.589999794960022, 1.5199999809265137, 1.9699997901916504, 2.3600001335144043, 1.8399999141693115, 1.71999990940094, 1.8799997568130493, 1.8299999237060547, 1.959999680519104, 1.840000033378601, 1.4299999475479126, 1.3099998235702515, 1.0299999713897705, 0.7500002384185791, 0.41999951004981995, 0.5999996066093445, 0.6499999165534973, 0.9500001072883606, 1.1099997758865356, 0.720000147819519, 0.9999997615814209, 1.2599999904632568, 1.4099997282028198, 1.179999828338623, 1.619999885559082, 1.7999999523162842, 1.9199999570846558, 1.6699998378753662, 1.7100000381469727, 1.6600000858306885, 1.4499998092651367, 1.5500003099441528, 1.6399999856948853, 1.459999918937683, 1.2199997901916504, 1.5299997329711914, 1.5899999141693115, 1.619999885559082, 1.559999942779541, 1.720000147819519, 1.2599997520446777, 1.1699997186660767, 1.419999599456787, 1.5700000524520874, 1.4799998998641968, 1.5199997425079346, 1.4199997186660767, 1.4100000858306885, 1.0099998712539673, 0.960000216960907, 1.0700000524520874, 1.010000228881836, 0.7500002384185791, 0.35999953746795654, 0.2399996668100357, 0.12000025808811188, 0.21999987959861755, 0.289999783039093, 0.23999996483325958, 0.8600002527236938, 1.2199996709823608, 1.499999761581421, 1.4599997997283936, 1.0499998331069946, 0.8600001931190491, 0.44999969005584717, 0.3199998140335083, 0.48000016808509827, 0.36000001430511475, 0.6899996995925903, 1.03000009059906, 1.010000228881836, 1.0500001907348633, 1.4600001573562622, 1.279999852180481, 1.1799997091293335, 1.1999998092651367, 1.4699997901916504, 1.350000023841858, 1.2399998903274536, 1.1299997568130493, 0.9999996423721313, 0.8500000238418579, 0.7999998927116394, 0.5599997043609619, 0.43999993801116943, 0.2899996042251587, 0.4099999666213989, 0.30999985337257385, 0.40999993681907654, 0.6099998354911804, 0.880000114440918, 1.169999599456787, 1.0599995851516724, 1.25, 1.3700000047683716, 1.5999999046325684, 1.7399998903274536, 1.6199997663497925, 1.4999998807907104, 1.7099997997283936, 2.069999933242798, 2.0299999713897705, 2.6499996185302734, 1.5999999046325684, 1.9299999475479126, 2.1599998474121094, 2.059999942779541, 2.3499999046325684, 2.0799999237060547, 2.4499998092651367, 2.0699996948242188, 2.3999998569488525, 2.429999828338623, 2.43999981880188, 2.3399999141693115, 2.059999942779541, 2.0199999809265137, 1.9399996995925903, 2.1599998474121094, 2.549999713897705, 3.0, 2.749999761581421, 3.180000066757202, 3.5099997520446777, 3.569999933242798, 2.8299996852874756, 2.319999933242798, 2.359999895095825, 3.6399998664855957, 3.049999952316284, 2.0899999141693115, 2.18999981880188, 2.3499999046325684, 2.5899999141693115, 2.799999952316284, 2.6999998092651367, 2.669999837875366, 2.669999837875366, 2.1999998092651367, 2.2799997329711914, 2.119999885559082, 2.879999876022339, 2.9699997901916504, 3.0199999809265137, 2.4799997806549072, 2.369999885559082, 2.429999828338623, 2.0399999618530273, 2.119999647140503, 2.069999933242798, 2.1499998569488525, 2.1399998664855957, 1.8199999332427979, 1.5199999809265137, 1.1799997091293335, 1.2199997901916504, 1.1399997472763062, 0.9199998378753662, 0.9000000953674316, 0.9900001287460327, 1.0699998140335083, 0.9800001978874207, 1.0399999618530273, 1.0299999713897705, 1.3800002336502075, 1.220000147819519, 1.089999794960022, 0.9900001883506775, 1.1199997663497925, 1.179999828338623, 1.739999771118164, 1.9099997282028198, 1.3299999237060547, 1.2999999523162842, 1.2899997234344482, 1.2599999904632568, 1.5699996948242188, 1.3499999046325684, 0.9399999380111694, 1.1800000667572021, 1.179999828338623, 1.2699998617172241, 1.2200000286102295, 1.5099997520446777, 1.6200000047683716, 1.6999999284744263, 1.5499998331069946, 1.559999942779541, 1.6400002241134644, 1.679999828338623, 1.5099998712539673, 1.600000023841858, 1.8299999237060547, 2.2099995613098145, 1.6699998378753662, 1.6600000858306885, 1.7199997901916504, 1.999999761581421, 2.169999837875366, 1.7300000190734863, 1.9300000667572021, 1.839999794960022, 1.7699999809265137, 1.4900000095367432, 2.450000047683716, 1.6699998378753662, 1.4000000953674316, 1.9000000953674316, 1.6999998092651367, 1.1499998569488525, 0.5299996137619019, 0.4999997317790985, 0.36000001430511475, 0.7899996638298035, 0.9299999475479126, 1.0799998044967651, 1.1799999475479126, 1.2499998807907104, 1.4700000286102295, 1.8000000715255737, 2.5199999809265137, 2.359999895095825, 2.240000009536743, 1.8199996948242188, 1.5399999618530273, 1.9399996995925903, 2.5699996948242188, 3.0899999141693115, 3.2899999618530273, 4.529999732971191, 4.229999542236328, 5.5099992752075195, 5.989999771118164, 5.739999771118164, 5.699999809265137, 5.210000038146973, 5.420000076293945, 4.600000381469727, 4.75, 4.730000019073486, 4.590000152587891, 5.119999885559082, 5.649999618530273, 5.589999675750732, 5.999999523162842, 5.960000038146973, 5.860000133514404, 6.21999979019165, 6.399999618530273, 6.869999408721924, 6.359999656677246, 7.3899993896484375, 7.980000019073486, 7.62999963760376, 6.180000305175781, 7.809999465942383, 8.399999618530273, 6.179999828338623, 5.809999942779541, 5.75, 5.480000019073486, 6.779999732971191, 6.189999580383301, 6.309999942779541, 6.349999904632568, 5.119999885559082, 4.949999809265137, 4.980000019073486, 4.53000020980835, 3.7199997901916504, 3.5699996948242188, 2.9799997806549072, 3.3999998569488525, 4.099999904632568, 3.7100000381469727, 3.6500000953674316, 3.0799999237060547, 2.8399999141693115, 2.5199999809265137, 1.8499999046325684, 2.2699999809265137, 2.9799997806549072, 2.7799997329711914, 2.440000057220459, 2.499999761581421, 1.7899999618530273, 2.119999885559082, 1.7899998426437378, 1.709999918937683, 1.9500000476837158, 2.6500000953674316, 3.179999828338623, 3.129999876022339, 2.7799999713897705, 2.6500000953674316, 2.819999933242798, 2.369999647140503, 1.9899998903274536, 1.9500000476837158, 2.0, 2.169999837875366, 2.0500001907348633, 2.18999981880188, 2.7299997806549072, 3.0199999809265137, 3.0299997329711914, 3.5099997520446777, 3.700000047683716, 4.179999828338623, 4.12999963760376, 4.079999923706055, 3.549999952316284, 2.9499998092651367, 2.7300000190734863, 4.119999885559082, 4.299999713897705, 3.130000114440918, 2.7799999713897705, 3.5799999237060547, 3.25, 4.339999675750732, 3.7899997234344482, 4.150000095367432, 3.419999599456787, 3.0999999046325684, 2.6999998092651367, 2.18999981880188, 2.5799999237060547, 2.6599998474121094, 2.2799997329711914, 2.1500000953674316, 1.6499998569488525, 2.119999647140503, 2.069999933242798, 1.659999966621399, 1.4399998188018799, 1.6400001049041748, 1.8499999046325684, 1.559999942779541, 1.5300002098083496, 1.7300000190734863, 1.2699999809265137, 1.0800000429153442, 0.7699999809265137, 0.5899994969367981, 0.7500001192092896, 0.639999508857727, 0.6099998950958252, 0.44000011682510376, 0.45999959111213684, 1.2400000095367432, 1.739999771118164, 1.6099997758865356, 1.46999990940094, 2.0799999237060547, 2.559999942779541, 3.6399998664855957, 3.319999933242798, 3.629999876022339, 3.549999952316284, 4.21999979019165, 4.599999904632568, 4.710000038146973, 4.409999847412109, 3.809999942779541, 3.4700000286102295, 3.419999837875366, 3.049999952316284, 3.0, 3.2699997425079346, 4.119999885559082, 3.929999828338623, 3.6999998092651367, 3.1599998474121094, 2.7100000381469727, 2.3199996948242188, 2.179999828338623, 2.3400001525878906, 2.25, 1.6899998188018799, 1.5500000715255737, 1.4900000095367432, 1.2300000190734863, 0.9900000095367432, 1.0399997234344482, 0.6299999952316284, 0.8600001335144043, 0.5799996852874756, 0.8599998950958252, 1.5999996662139893, 1.8999998569488525, 1.239999771118164, 1.7199997901916504, 2.0299997329711914, 2.439999580383301, 3.1999998092651367, 3.419999837875366, 2.919999837875366, 2.93999981880188, 2.8400001525878906, 2.990000009536743, 3.7799997329711914, 2.8999996185302734, 3.169999837875366, 3.249999761581421, 3.2599997520446777, 3.109999656677246, 4.189999580383301, 3.1600000858306885, 3.06000018119812, 2.950000047683716, 3.4200000762939453, 3.2699997425079346, 2.8399999141693115, 2.9600000381469727, 2.4600000381469727, 1.8799998760223389, 2.819999933242798, 2.7299997806549072, 3.1600000858306885, 3.75, 3.8299999237060547, 4.239999771118164, 3.799999713897705, 2.690000057220459, 2.119999885559082, 1.959999918937683, 1.9200000762939453, 2.369999885559082, 1.7799999713897705, 1.7100002765655518, 2.370000123977661, 1.929999828338623, 5.71999979019165, 5.009999752044678, 4.399999618530273, 3.929999589920044, 4.859999656677246, 4.979999542236328, 4.849999904632568, 5.130000114440918, 5.059999465942383, 5.610000133514404, 5.0199995040893555, 5.650000095367432, 6.109999656677246, 6.5799994468688965, 6.029999732971191, 5.389999866485596, 5.710000038146973, 5.869999885559082, 6.440000057220459, 6.189999580383301, 6.570000171661377, 6.71999979019165, 6.679999828338623, 6.619999885559082, 6.489999771118164, 5.579999923706055, 6.109999656677246, 6.449999809265137, 6.519999980926514, 6.920000076293945, 7.53000020980835, 7.149999618530273, 6.669999599456787, 6.0, 6.110000133514404, 6.049999713897705, 6.059999942779541, 6.400000095367432, 6.299999713897705, 6.449999809265137, 6.149999618530273, 6.5199995040893555, 7.190000057220459, 7.199999809265137, 6.980000019073486, 6.5799994468688965, 6.569999694824219, 6.929999828338623, 7.149999618530273, 7.2699995040893555, 6.869999885559082, 7.649999618530273, 7.309999465942383, 7.429999828338623, 7.769999980926514, 7.34999942779541, 7.71999979019165, 7.599999904632568, 7.569999694824219, 7.71999979019165, 7.449999809265137, 7.139999866485596, 7.039999961853027, 7.21999979019165, 7.329999923706055, 7.529999732971191, 7.319999694824219, 6.979999542236328, 6.8899993896484375, 6.759999752044678, 6.809999942779541, 6.730000019073486, 6.480000019073486, 6.429999351501465, 5.289999961853027, 5.529999732971191, 5.869999885559082, 6.480000019073486, 6.559999465942383, 6.460000038146973, 6.639999866485596, 6.420000076293945, 6.570000171661377, 6.249999523162842, 5.539999961853027, 5.779999732971191, 6.559999465942383, 6.96999979019165, 6.899999618530273, 6.939999580383301, 6.529999732971191, 6.239999771118164, 6.329999923706055, 6.440000057220459, 6.799999713897705, 7.099999904632568, 6.889999866485596, 6.96999979019165, 7.069999694824219, 7.949999809265137, 6.869999885559082, 7.389999866485596, 6.880000114440918, 7.429999828338623, 8.269999504089355, 8.350000381469727, 8.069999694824219, 7.789999485015869, 8.829999923706055, 8.819999694824219, 8.6899995803833, 8.75, 8.800000190734863, 8.579998970031738, 9.269999504089355, 9.549999237060547, 10.059999465942383, 10.269999504089355, 10.779999732971191, 10.179999351501465, 9.50999927520752, 9.180000305175781, 8.610000610351562, 8.9399995803833, 9.239999771118164, 9.829999923706055, 10.420000076293945, 10.739999771118164, 11.179999351501465, 10.59000015258789, 10.59000015258789, 10.75, 11.109999656677246, 11.210000038146973, 11.460000038146973, 11.619998931884766, 11.739999771118164, 12.09999942779541, 11.59000015258789, 12.199999809265137, 12.630000114440918, 12.44999885559082, 13.210000038146973, 13.359999656677246, 13.399998664855957, 12.960000038146973, 12.770000457763672, 13.260000228881836, 13.170000076293945, 13.199999809265137, 12.529999732971191, 12.519999504089355, 12.169999122619629, 12.730000495910645, 12.669999122619629, 12.480000495910645, 12.639999389648438, 12.84999942779541, 13.3100004196167, 14.00999927520752, 13.690000534057617, 13.890000343322754, 13.629999160766602, 13.519999504089355, 14.120000839233398, 13.899998664855957, 14.299999237060547, 14.079998970031738, 14.180000305175781, 14.770000457763672, 15.129998207092285, 14.479999542236328, 14.479999542236328, 15.109999656677246, 15.110000610351562, 14.970000267028809, 14.84999942779541, 15.220000267028809, 15.679999351501465, 15.8100004196167, 15.469999313354492, 15.119998931884766, 15.159998893737793, 14.15999984741211, 13.889999389648438, 14.209999084472656, 14.549999237060547, 14.789999008178711, 14.669999122619629, 14.260000228881836, 13.190000534057617, 13.359999656677246, 14.009998321533203, 13.65999984741211, 13.309999465942383, 13.65999984741211, 13.279999732971191, 12.679999351501465, 12.030000686645508, 10.979999542236328, 11.179999351501465, 10.869999885559082, 9.970000267028809, 9.579998970031738, 9.680000305175781, 10.020000457763672, 10.24000072479248, 10.119999885559082, 11.619999885559082, 10.449999809265137, 10.59999942779541, 10.639999389648438, 9.6899995803833, 9.680000305175781, 10.230000495910645, 10.679999351501465, 11.180000305175781, 11.119999885559082, 11.59999942779541, 10.90000057220459, 11.25999927520752, 10.829999923706055, 11.380000114440918, 11.319998741149902, 10.15999984741211, 10.069999694824219, 10.199999809265137, 8.529999732971191, 10.119999885559082, 9.390000343322754, 8.329999923706055, 8.180000305175781, 7.680000305175781, 7.449999809265137, 7.710000038146973, 7.460000038146973, 7.920000076293945, 7.800000190734863, 8.529999732971191, 8.130000114440918, 8.049999237060547, 7.820000171661377, 7.329999923706055, 7.630000114440918, 7.730000019073486, 7.299999713897705, 7.049999713897705, 6.489999771118164, 6.429999828338623, 5.289999961853027, 5.420000076293945, 4.619999885559082, 4.509999752044678, 4.339999675750732, 3.7799997329711914, 3.619999647140503, 3.1599998474121094, 3.570000171661377, 3.4599997997283936, 3.129999876022339, 3.2099997997283936, 3.6999998092651367, 3.5799999237060547, 3.1499998569488525, 3.5199999809265137, 3.629999876022339, 3.93999981880188, 4.279999732971191, 4.279999732971191, 3.8899998664855957, 4.049999713897705, 4.389999866485596, 4.529999732971191, 4.699999809265137, 4.37999963760376, 4.430000305175781, 4.339999675750732, 3.869999647140503, 3.5, 3.490000009536743, 3.429999828338623, 3.319999933242798, 3.190000057220459, 2.7799997329711914, 2.6600000858306885, 2.2699999809265137, 2.0699996948242188, 2.049999952316284, 1.989999771118164, 2.1500000953674316, 2.0999999046325684, 2.0399999618530273, 1.9299997091293335, 1.7699998617172241, 1.4299999475479126, 1.3099998235702515, 1.369999885559082, 1.2599998712539673, 1.2199997901916504, 1.1499998569488525, 1.2899996042251587, 1.3199999332427979, 1.2199996709823608, 1.1499998569488525, 1.0899996757507324, 1.0900001525878906, 1.1500000953674316, 0.6199996471405029, 0.5599998831748962, 0.35999995470046997, 0.25999966263771057, 0.30000022053718567, 0.2700001895427704, 0.3799999952316284, 0.7499996423721313, 0.9799995422363281, 1.7999999523162842, 2.049999952316284, 2.3899996280670166, 2.239999771118164, 1.9199998378753662, 2.0799999237060547, 2.619999885559082, 1.869999885559082, 1.779999852180481, 2.1100001335144043, 2.629999876022339, 2.8999998569488525, 2.679999828338623, 3.3199996948242188, 3.319999933242798, 2.5999999046325684, 2.8999996185302734, 2.569999933242798, 2.369999885559082, 2.7899999618530273, 2.919999599456787, 2.429999828338623, 2.6999998092651367, 2.379999876022339, 3.309999942779541, 2.559999942779541, 2.809999942779541, 3.0699996948242188, 2.7200000286102295, 2.680000066757202, 3.1499998569488525, 2.6999998092651367, 2.68999981880188, 2.7299997806549072, 2.7200000286102295, 2.7200000286102295, 2.7200000286102295, 2.5799999237060547, 2.7200000286102295, 2.4800000190734863, 2.179999828338623, 1.78000009059906, 1.8900002241134644, 2.7199997901916504, 3.049999952316284, 2.5, 2.240000009536743, 3.289999485015869, 3.180000066757202, 3.2099997997283936, 2.559999704360962, 2.7699999809265137, 2.009999990463257, 2.869999885559082, 3.049999952316284, 2.8499999046325684, 3.069999933242798, 3.5799999237060547, 3.9800000190734863, 4.360000133514404, 4.759999752044678, 5.159999847412109, 6.039999961853027, 6.869999885559082, 6.449999809265137, 6.789999961853027, 7.609999656677246, 7.71999979019165, 8.050000190734863, 7.800000190734863, 9.179999351501465, 8.670000076293945, 7.269999980926514, 8.100000381469727, 8.709999084472656, 8.350000381469727, 8.779999732971191, 8.699999809265137, 8.09000015258789, 8.029999732971191, 7.049999713897705, 6.729999542236328, 7.800000190734863, 7.319999694824219, 7.539999485015869, 7.559999942779541, 7.5199995040893555, 7.62999963760376, 6.210000038146973, 5.630000114440918, 6.489999771118164, 7.649999618530273, 6.7099995613098145, 7.050000190734863, 5.339999675750732, 4.71999979019165, 5.369999885559082, 6.009999752044678, 6.139999866485596, 5.480000019073486, 4.349999904632568, 6.259999752044678, 6.989999771118164, 5.659999847412109, 5.279999732971191, 5.619999885559082, 5.190000057220459, 5.650000095367432, 4.829999923706055, 5.359999656677246, 5.0799994468688965, 4.909999847412109, 4.359999656677246, 4.559999465942383, 4.440000057220459, 4.189999580383301, 4.699999809265137, 5.109999656677246, 5.059999465942383, 4.820000171661377, 4.889999866485596, 4.539999961853027, 4.029999732971191, 4.259999752044678, 4.099999904632568, 3.879999876022339]\n",
      "0.19023867108472603\n",
      "0.30845926309459626\n",
      "3.7899999618530273\n"
     ]
    }
   ],
   "source": [
    "print(y_t)\n",
    "mseloss = 0\n",
    "maeloss = 0\n",
    "maxloss = 0\n",
    "for i in range(1, len(y_t)):\n",
    "    mseloss += (y_t[i - 1] - y_t[i]) ** 2\n",
    "    maeloss += abs(y_t[i - 1] - y_t[i])\n",
    "    if abs(y_t[i - 1] - y_t[i]) > maxloss:\n",
    "        maxloss = abs(y_t[i - 1] - y_t[i])\n",
    "print(mseloss / len(y_t))\n",
    "print(maeloss / len(y_t))\n",
    "print(maxloss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 假设 predictions 和 actual_values 已经定义\n",
    "# predictions 是模型的预测值，actual_values 是真实值\n",
    "import matplotlib.pyplot as plt\n",
    "actual_values = y_t\n",
    "predictions = y_p\n",
    "length = 1000\n",
    "actual_values = actual_values[:length]\n",
    "predictions = predictions[:length]\n",
    "\n",
    "# 创建散点图\n",
    "plt.scatter(actual_values, predictions, color='blue', label='Actual vs Predicted')\n",
    "\n",
    "# 添加标签和标题\n",
    "plt.xlabel('Actual Values')\n",
    "plt.ylabel('Predicted Values')\n",
    "plt.title('Actual vs Predicted Values')\n",
    "\n",
    "# 添加对角线，用于比较完美预测的情况\n",
    "plt.plot([min(actual_values), max(actual_values)], [min(actual_values), max(actual_values)], linestyle='--', color='red', linewidth=2, label='Perfect Prediction')\n",
    "\n",
    "# 显示图例\n",
    "plt.legend()\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f37d013ff80>]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length = 100\n",
    "start = 30\n",
    "x = [i for i in range(length)]\n",
    "plt.figure(figsize=(20, 6))\n",
    "plt.plot(x, y_p[start: start + length], color=\"red\")\n",
    "plt.plot(x, y_t[start: start + length])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([35279, 134, 3])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "dxy-top1hik",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
